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Sudarshan Dutta
International Plant Nutrition Institute, South Asia (East India and Bangladesh) Program, India and African Plant Nutrition Institute, Benguerir 43150, Morocco

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Journal article
Published: 06 August 2021 in Plants
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Rice is the lifeline for more than half of the world population, and in India, in view of its huge demand in the country, farmers adopt a rice–rice cropping system where the irrigation facility is available. As rice is a nutrient-exhausting crop, sustainable productivity of rice–rice cropping system greatly depends on appropriate nutrient management in accordance with the inherent soil fertility. The application of an ample dose of fertilizer is the key factor for maintaining sustainable rice yields and nutrient balance of the soil. Considering the above facts, an experiment was conducted on nutrient management in a rice–rice cropping system at the university farm of Visva-Bharati, situated in a sub-tropical climate under the red and lateritic belt of the western part of West Bengal, India, during two consecutive years (2014–2016). The experiment was laid out in a Randomized Completely Block Design with 12 treatments and three replications, with different rates of N:P:K:Zn:S application in both of the growing seasons, namely, kharif and Boro. The recommended (ample) dose of nutrients was 80:40:40:25:20 and 120:60:60:25:20 kg ha−1 of N:P2O5:K2O:Zn:S in the Kharif and Boro season, respectively. A high yielding variety, named MTU 7029, and a hybrid, Arize 6444 GOLD, were taken in the Kharif and Boro seasons, respectively. The results clearly indicated that the application of a recommended dose of nutrients showed its superiority over the control (no fertilizer application) in the expression of growth characters, yield attributes, yields, and nutrient uptake of Kharif as well as Boro rice. Out of the all treatments, the best result was found in the treatment where the ample dose of nutrients was applied, resulting in maximum grain yield in both the Kharif (5.6 t ha−1) and Boro (6.6 t ha−1) season. The corresponding yield attributes for the same treatment in the Kharif (panicles m−2: 247.9; grains panicle−1: 132.0; spikelets panicle−1: 149.6; test weight: 23.8 g; and panicle length: 30.6 cm) and Boro (panicles m−2: 281.6; grains panicle−1: 142.7; spikelets panicle−1: 157.2; test weight: 24.8 g; and panicle length: 32.8 cm) season explained the maximum yield in this treatment. Further, a reduction or omission of individual nutrients adversely impacted on the above traits and resulted in a negative balance of the respective nutrients. The study concluded that the application of a recommended dose of nutrients was essential for proper nutrient balance and sustainable yields in the rice–rice cropping system.

ACS Style

Tanmoy Shankar; Ganesh Malik; Mahua Banerjee; Sudarshan Dutta; Sagar Maitra; Subhashisa Praharaj; Masina Sairam; Duvvada Kumar; Eldessoky Dessoky; Mohamed Hassan; Ismail Ismail; Tarek Saif; Milan Skalicky; Marian Brestic; Akbar Hossain. Productivity and Nutrient Balance of an Intensive Rice–Rice Cropping System Are Influenced by Different Nutrient Management in the Red and Lateritic Belt of West Bengal, India. Plants 2021, 10, 1622 .

AMA Style

Tanmoy Shankar, Ganesh Malik, Mahua Banerjee, Sudarshan Dutta, Sagar Maitra, Subhashisa Praharaj, Masina Sairam, Duvvada Kumar, Eldessoky Dessoky, Mohamed Hassan, Ismail Ismail, Tarek Saif, Milan Skalicky, Marian Brestic, Akbar Hossain. Productivity and Nutrient Balance of an Intensive Rice–Rice Cropping System Are Influenced by Different Nutrient Management in the Red and Lateritic Belt of West Bengal, India. Plants. 2021; 10 (8):1622.

Chicago/Turabian Style

Tanmoy Shankar; Ganesh Malik; Mahua Banerjee; Sudarshan Dutta; Sagar Maitra; Subhashisa Praharaj; Masina Sairam; Duvvada Kumar; Eldessoky Dessoky; Mohamed Hassan; Ismail Ismail; Tarek Saif; Milan Skalicky; Marian Brestic; Akbar Hossain. 2021. "Productivity and Nutrient Balance of an Intensive Rice–Rice Cropping System Are Influenced by Different Nutrient Management in the Red and Lateritic Belt of West Bengal, India." Plants 10, no. 8: 1622.

Journal article
Published: 09 July 2021 in Biosystems Engineering
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This study evaluated a novel smartphone-based soil image segmentation technique and subsequent machine learning (ML) optimization methodology with a set of soil images for rapidly predicting soil organic matter (SOM) with minimal soil processing. A smartphone and a custom-made box were used to capture images for 90 soil samples, collected from three different agroclimatic zones of West Bengal, India under three different illumination conditions. To offset the impact of variable illumination, the reflectance component of the image was recovered by removing the illumination from the image. Further, to deceive the ML model without distorting the soil image, an adversarial image was generated by adding Gaussian noise to the image. A Tree-based Pipeline Optimisation Tool was used to find an optimum ML stacking scheme using six different ML models. Model validation statistics indicated that reflectance image-extracted sub-colour space could predict SOM with reasonable accuracy (R2 = 0.88, RMSE = 0.28%) using original images in stack one. Moreover, the sub-colour space using perturbed images in stack one could sense noise, worsening the model validation (R2 = 0.79, RMSE = 0.36%). Conversely, seven out of eight tested colour spaces in stack two were unable to sense the image noise, producing higher validation performance than the original images. The proposed smartphone-based image acquisition setup combined with the computer vision and ML pipeline produced an important advance in affordable optical tool-based SOM prediction with significant time and cost savings. More research is warranted to extend this approach by incorporating field images of variable soil types taken under variable illuminations.

ACS Style

Srikanth Gorthi; R.K. Swetha; Somsubhra Chakraborty; Bin Li; David C. Weindorf; Sudarshan Dutta; Hirak Banerjee; Krishnendu Das; Kaushik Majumdar. Soil organic matter prediction using smartphone-captured digital images: Use of reflectance image and image perturbation. Biosystems Engineering 2021, 209, 154 -169.

AMA Style

Srikanth Gorthi, R.K. Swetha, Somsubhra Chakraborty, Bin Li, David C. Weindorf, Sudarshan Dutta, Hirak Banerjee, Krishnendu Das, Kaushik Majumdar. Soil organic matter prediction using smartphone-captured digital images: Use of reflectance image and image perturbation. Biosystems Engineering. 2021; 209 ():154-169.

Chicago/Turabian Style

Srikanth Gorthi; R.K. Swetha; Somsubhra Chakraborty; Bin Li; David C. Weindorf; Sudarshan Dutta; Hirak Banerjee; Krishnendu Das; Kaushik Majumdar. 2021. "Soil organic matter prediction using smartphone-captured digital images: Use of reflectance image and image perturbation." Biosystems Engineering 209, no. : 154-169.

Journal article
Published: 24 May 2021 in Agricultural Systems
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Smallholder farmers of the Eastern Indo-Gangetic Plains (EIGP) of South Asia rely mainly on cereal-based cropping systems to meet the food and nutritional demand and support their livelihood. Yet the productivity of the major cereals - rice, wheat, and maize - in the region are far lower than their potential. Nutrient management plays a crucial role in improving cereal yields and economic return, and continued improvement in nutrient management practices and their on-farm implementation is required to develop locally relevant solutions that are site-specific, easy-to-develop and geared towards system resilience. The objective of the study was to conduct the comparative assessment of three nutrient management strategies for the three major cereals considering productivity, profitability and nutrient use efficiencies (NUE); estimate their potential yields and yield gaps; and explain the causes of yield variability across farmer-participatory on-farm trials in the EIGP of Nepal. We compared three nutrient management strategies (farmer's fertilizer practice- FP, government recommendation -GR, and Nutrient Expert®- NE-based recommendation), in 600 on-farm trials. We used the NE DSS tool, APSIM – a cropping system simulation model, and machine learning (ML) approaches (Linear Mixed Effect model -LME; and Random Forest model - RF) for the three cereals using data from those trials. The NE and APSIM were chosen due to simplicity in use and their wider evaluation and application in fertilizer recommendation yield prediction; RF was chosen due to its robustness in predictive ability and identifying and ranking factors determining yield or other variables of interest. The NE-based fertilizer recommendations for maize, wheat and rice increased yield by about 3.5, 1.4, and 1.3 t ha−1 respectively, increased profits, and improved NUE over FP or GR. The risk analysis showed that at a given probability level, NE always resulted in higher yields of all cereals than GR or FP. APSIM identified 25th June as optimum transplanting date for rice and 10th December as optimum sowing date for maize and wheat and simulated long-term average potential yield of 7–7.5, 5–5.5 and 13–13.3 t ha−1 respectively for rice, wheat and maize. There were larger yield gaps between PY and FP (2.6–8.5 t ha−1) than PY and NE (2.0–3.7 t ha−1) across crops and villages. The LME model showed highly significant treatment and location effects for grain yield of all cereals. The point estimate of the difference for grain yield as estimated by Tukey's HSD test was highest for NE-FP and lowest for GR-FP for all crops. The RF model identified grain N uptake for rice and grain P and K uptakes for wheat and maize as most influential factors contributing to their grain yield under each nutrient management strategy. The NE-based nutrient management had significant effects over FP and GR leading to positive changes on yield and economic performance under varied growing environments. These findings based on novel tools and approaches have important policy implications for increasing food security and profits from the major cereals by refining or improving the GR or FP and increasing their NUE in Nepal. Studies with larger sample size across varied agro-climatic zones in the EIGP and much of South Asia would help policy makers consider DSS tools and ML approaches suitable for upscaling and large-scale adoption by smallholder farmers.

ACS Style

Jagadish Timsina; Sudarshan Dutta; Krishna Prasad Devkota; Somsubhra Chakraborty; Ram Krishna Neupane; Sudarshan Bishta; Lal Prasad Amgain; Vinod K. Singh; Saiful Islam; Kaushik Majumdar. Improved nutrient management in cereals using Nutrient Expert and machine learning tools: Productivity, profitability and nutrient use efficiency. Agricultural Systems 2021, 192, 103181 .

AMA Style

Jagadish Timsina, Sudarshan Dutta, Krishna Prasad Devkota, Somsubhra Chakraborty, Ram Krishna Neupane, Sudarshan Bishta, Lal Prasad Amgain, Vinod K. Singh, Saiful Islam, Kaushik Majumdar. Improved nutrient management in cereals using Nutrient Expert and machine learning tools: Productivity, profitability and nutrient use efficiency. Agricultural Systems. 2021; 192 ():103181.

Chicago/Turabian Style

Jagadish Timsina; Sudarshan Dutta; Krishna Prasad Devkota; Somsubhra Chakraborty; Ram Krishna Neupane; Sudarshan Bishta; Lal Prasad Amgain; Vinod K. Singh; Saiful Islam; Kaushik Majumdar. 2021. "Improved nutrient management in cereals using Nutrient Expert and machine learning tools: Productivity, profitability and nutrient use efficiency." Agricultural Systems 192, no. : 103181.

Journal article
Published: 15 March 2021 in Sustainability
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Nutrient management is critical for rice farming because the crop is grown under diverse conditions, and in most cases, the existing nutrient management practices fail to achieve an attainable yield target. During recent years site specific nutrient management gained importance for a target yield with maximum nutrient use efficiency. Sufficient research work has not been carried out in this direction so far in the rice–rice–pulse (black gram) sequential cropping system under the red and lateritic belt of West Bengal, India. A multi-locational field experiment was conducted from July 2013 to June 2015 at three different locations, namely, Guskara (Burdwan district) and Benuriya (Birbhum district) villages in farmers’ fields and at the university farm of Visva-Bharati, Sriniketan, West Bengal, India. The performance of nutrients was tested by providing ample doses of N, P, K, S, and Zn compared to the omission of these nutrients. The growth parameters, such as crop biomass production, leaf area index, and number of tillers, and yield attributes and yield were influenced by nutrient management treatments. Application of 100% of N, P, K, S, and Zn resulted in its superiority to other nutrient management options studied, and a similar trend was also noted with the treatment in the expression of nutrient use efficiency (NUE) and nutrient response (NR). The available N, P, K, S, and Zn contents in soil increased steadily due to the increase in fertilizer application. The study concluded that optimization of NPK in the rice–rice–pulse cropping system on target yield along with need-based S and Zn application was beneficial for higher productivity.

ACS Style

Tanmoy Shankar; Mahua Banerjee; Ganesh Malik; Sudarshan Dutta; Debtanu Maiti; Sagar Maitra; Hesham Alharby; Atif Bamagoos; Akbar Hossain; Ismail Ismail; Ayman EL Sabagh. The Productivity and Nutrient Use Efficiency of Rice–Rice–Black Gram Cropping Sequence Are Influenced by Location Specific Nutrient Management. Sustainability 2021, 13, 3222 .

AMA Style

Tanmoy Shankar, Mahua Banerjee, Ganesh Malik, Sudarshan Dutta, Debtanu Maiti, Sagar Maitra, Hesham Alharby, Atif Bamagoos, Akbar Hossain, Ismail Ismail, Ayman EL Sabagh. The Productivity and Nutrient Use Efficiency of Rice–Rice–Black Gram Cropping Sequence Are Influenced by Location Specific Nutrient Management. Sustainability. 2021; 13 (6):3222.

Chicago/Turabian Style

Tanmoy Shankar; Mahua Banerjee; Ganesh Malik; Sudarshan Dutta; Debtanu Maiti; Sagar Maitra; Hesham Alharby; Atif Bamagoos; Akbar Hossain; Ismail Ismail; Ayman EL Sabagh. 2021. "The Productivity and Nutrient Use Efficiency of Rice–Rice–Black Gram Cropping Sequence Are Influenced by Location Specific Nutrient Management." Sustainability 13, no. 6: 3222.

Journal article
Published: 25 February 2021 in Journal of Plant Nutrition
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Nepal is a major rice producer of South Asia, feeding more than 20 million people of the country and abroad. However, productivity and profitability of rice are low in Nepal compared to other regional countries. Large yield gaps exist between attainable and farmers’ yields and nutrient management is identified as one of the major reasons. Nutrient Expert® (NE), a decision-support tool based on site-specific nutrient management (SSNM) principles has been validated and applied in many countries of Asia and Africa as new recommendation protocol for nutrient management in selected crops, including rice. Present study used NE® Rice as nutrient management protocol in farmers’ fields across Terai and mid-hills regions of Nepal during 2014–2018. The study revealed that NE-based fertilizer recommendations resulted in increase in yield over 2.0 t.ha−1 (p ≤ 0.05) and double the profits compared to existing blanket fertilizer recommendation, and farmers’ fertilizer practice. Due to large variations in slope, altitude, soil, and management, performance of NE® varied across locations. Its performance was better in Terai due to flat lands and less variations in soil types, compared to sloping lands and varied soils of mid-hills. NE tool provided adequate guidance to apply the required rate of fertilizer that matched the crop requirement and soil nutrient supply of each farmer fields. The novelty of the study is introduction of a dynamic fertilizer recommendation approach that can supplement the existing static blanket recommendation system. We conclude that Nutrient Expert® - Rice can be considered as an effective tool for nutrient recommendation for rice in Nepal.

ACS Style

Lal Prasad Amgain; Jagadish Timsina; Sudarshan Dutta; Kaushik Majumdar. Nutrient expert® rice - an alternative fertilizer recommendation strategy to improve productivity, profitability and nutrient use efficiency of rice in Nepal. Journal of Plant Nutrition 2021, 1 -16.

AMA Style

Lal Prasad Amgain, Jagadish Timsina, Sudarshan Dutta, Kaushik Majumdar. Nutrient expert® rice - an alternative fertilizer recommendation strategy to improve productivity, profitability and nutrient use efficiency of rice in Nepal. Journal of Plant Nutrition. 2021; ():1-16.

Chicago/Turabian Style

Lal Prasad Amgain; Jagadish Timsina; Sudarshan Dutta; Kaushik Majumdar. 2021. "Nutrient expert® rice - an alternative fertilizer recommendation strategy to improve productivity, profitability and nutrient use efficiency of rice in Nepal." Journal of Plant Nutrition , no. : 1-16.

Journal article
Published: 19 January 2021 in Agricultural Systems
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The shock of Coronavirus Disease 2019 (COVID-19) has disrupted food systems worldwide. Such disruption, affecting multiple systems interfaces in smallholder agriculture, is unprecedented and needs to be understood from multi-stakeholder perspectives. The multiple loops of causality in the pathways of impact renders the system outcomes unpredictable. Understanding the nature of such unpredictable pathways is critical to identify present and future systems intervention strategies. Our study aims to explore the multiple pathways of present and future impact created by the pandemic and “Amphan” cyclonic storm on smallholder agricultural systems. Also, we anticipate the behaviour of the systems elements under different realistic scenarios of intervention. We explored the severity and multi-faceted impacts of the pandemic on vulnerable smallholder agricultural production systems through in-depth interactions with key players at the micro-level. It provided contextual information, and revealed critical insights to understand the cascading effect of the pandemic and the cyclone on farm households. We employed thematic analysis of in-depth interviews with multiple stakeholders in Sundarbans areas in eastern India, to identify the present and future systems outcomes caused by the pandemic, and later compounded by “Amphan”. The immediate adaptation strategies of the farmers were engaging family labors, exchanging labors with neighbouring farmers, borrowing money from relatives, accessing free food rations, replacing dead livestock, early harvesting, and reclamation of waterbodies. The thematic analysis identified several systems elements, such as harvesting, marketing, labor accessibility, among others, through which the impacts of the pandemic were expressed. Drawing on these outputs, we employed Mental Modeler, a Fuzzy-Logic Cognitive Mapping tool, to develop multi-stakeholder mental models for the smallholder agricultural systems of the region. Analysis of the mental models indicated the centrality of “Kharif” (monsoon) rice production, current farm income, and investment for the next crop cycle to determine the pathways and degree of the dual impact on farm households. Current household expenditure, livestock, and soil fertility were other central elements in the shared mental model. Scenario analysis with multiple stakeholders suggested enhanced market access and current household income, sustained investment in farming, rapid improvement in affected soil, irrigation water and livestock as the most effective strategies to enhance the resilience of farm families during and after the pandemic. This study may help in formulating short and long-term intervention strategies in the post-pandemic communities, and the methodological approach can be used elsewhere to understand perturbed socioecological systems to formulate anticipatory intervention strategies based on collective wisdom of stakeholders.

ACS Style

Rupak Goswami; Kalyan Roy; Sudarshan Dutta; Krishnendu Ray; Sukamal Sarkar; Koushik Brahmachari; Manoj Kr. Nanda; Mohammed Mainuddin; Hirak Banerjee; Jagadish Timsina; Kaushik Majumdar. Multi-faceted impact and outcome of COVID-19 on smallholder agricultural systems: Integrating qualitative research and fuzzy cognitive mapping to explore resilient strategies. Agricultural Systems 2021, 189, 103051 -103051.

AMA Style

Rupak Goswami, Kalyan Roy, Sudarshan Dutta, Krishnendu Ray, Sukamal Sarkar, Koushik Brahmachari, Manoj Kr. Nanda, Mohammed Mainuddin, Hirak Banerjee, Jagadish Timsina, Kaushik Majumdar. Multi-faceted impact and outcome of COVID-19 on smallholder agricultural systems: Integrating qualitative research and fuzzy cognitive mapping to explore resilient strategies. Agricultural Systems. 2021; 189 ():103051-103051.

Chicago/Turabian Style

Rupak Goswami; Kalyan Roy; Sudarshan Dutta; Krishnendu Ray; Sukamal Sarkar; Koushik Brahmachari; Manoj Kr. Nanda; Mohammed Mainuddin; Hirak Banerjee; Jagadish Timsina; Kaushik Majumdar. 2021. "Multi-faceted impact and outcome of COVID-19 on smallholder agricultural systems: Integrating qualitative research and fuzzy cognitive mapping to explore resilient strategies." Agricultural Systems 189, no. : 103051-103051.

Research article
Published: 05 January 2021 in Journal of Plant Nutrition
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Rice-maize is an emerging cropping system in South Asia that plays significant role in terms of achieving food security in the region. However, achievement of attainable yield in these two crops is often a constrain due to imbalanced and inadequate use of essential plant nutrients. Understanding the contribution of different nutrients (N, P, K, S and Zn) toward yields of hybrid rice—hybrid maize cropping system in calcareous soil is a need for large number of smallholder farming systems. A four seasons study was conducted with an objective to develop further knowledge on crop productivity and nutrient performance indicators in this newly adapted emerging farming system. Replicated nutrient omission trials were conducted at Bihar, India. At the calcareous soil, omission of the nutrients reduced yields, and N was the most limiting nutrient followed by P and K. Omission of Zn impacted crop yields more than S omission, effect was more prominent in hybrid maize. Nutrient uptake in the cropping system was declined by 58%, 37%, 34%, 31% and 25% for N, P, K, S, and Zn, respectively, when these nutrients were systematically removed from fertilization schedule. Sustainable Yield Index (SYI) for cropping system was highest in the ample balanced fertilizer treatment. Post-harvest soil nutrient availability declined in the nutrient omission plots as compared to the initial soil status. We included additional treatments of ample balanced nutrient application and unfertilized check where hybrid cultivars were replaced by inbred varieties of rice and maize. Cropping system productivity highlighted the synergistic effect of seed and nutrients. The unfertilized checks reduced yield by 9 t/ha and 5 t/ha for the hybrid and inbred cropping systems, respectively. Results from present study conclude that adoption of hybrids in rice-maize system and balanced nutrient management are the best management practices for sustainable food production.

ACS Style

Shiveshwar Pratap Singh; Sudarshan Kumar Dutta; Shankar Jha; Shiv Shankar Prasad; Sanjay Kumar Chaudhary; Vishal Sahi; Kaushik Majumdar. Nutrient management in calcareous soil improves rice–maize sustainable yield index, performance indicators. Journal of Plant Nutrition 2021, 1 -16.

AMA Style

Shiveshwar Pratap Singh, Sudarshan Kumar Dutta, Shankar Jha, Shiv Shankar Prasad, Sanjay Kumar Chaudhary, Vishal Sahi, Kaushik Majumdar. Nutrient management in calcareous soil improves rice–maize sustainable yield index, performance indicators. Journal of Plant Nutrition. 2021; ():1-16.

Chicago/Turabian Style

Shiveshwar Pratap Singh; Sudarshan Kumar Dutta; Shankar Jha; Shiv Shankar Prasad; Sanjay Kumar Chaudhary; Vishal Sahi; Kaushik Majumdar. 2021. "Nutrient management in calcareous soil improves rice–maize sustainable yield index, performance indicators." Journal of Plant Nutrition , no. : 1-16.

Original research article
Published: 02 September 2020 in Frontiers in Plant Science
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It is critical to understand nutrient dynamics within different plant parts to correctly fine-tune agronomic advices, and to update breeding programs for increasing nutrient use efficiencies and yields. Farmer’s field-based research was conducted to assess the effects of nitrogen (N), phosphorus (P), and potassium (K) levels on dry matter and nutrient accumulation, partitioning, and remobilization dynamics in three popular maize (Zea mays L.) hybrids (P3522, P3396, and Rajkumar) over two years in an alluvial soil of West Bengal, India. Experimental results revealed that NPK rates as well as different cultivars significantly (p ≤ 0.05) influenced the dry matter accumulation (DMA) in different plant parts of maize at both silking and physiological maturity. The post-silking dry matter accumulation (PSDMA) and post-silking N, P, and K accumulations (PSNA, PSPA, PSKA) were highest in cultivar P3396. However, cultivar P3522 recorded the highest nutrient remobilizations and contributions to grain nutrient content. Total P and K accumulation were highest with 125% of the recommended dose of fertilizer (RDF) while total N accumulation increased even after 150% RDF (100% RDF is 200 kg N, 60 kg P2O5, and 60 kg K2O ha–1 for the study region). Application of 125% RDF was optimum for PSDMA. The PSNA continued to increase up to 150% RDF while 125% RDF was optimum for PSPA. Cultivar differences significantly affected both remobilization efficiency (RE) and contribution to grain nutrient content for all tested macronutrients (N, P, and K). In general, RE as well as contribution to grain nutrient content was highest at 125% RDF for N and K, and at 100% RDF for P (either significantly or at par with other rates) for plots receiving nutrients. For all tested cultivars, nutrient remobilization and contribution to grain nutrient content was highest under nutrient-omission plots and absolute control plots. Both year and cultivar effects were non-significant for both grain and stover yields of maize. Application of 75% RDF was sufficient to achieve the attainable yield at the study location. The cultivar P3522 showed higher yield over both P3396 and Rajkumar, irrespective of fertilizer doses, although, the differences were not statistically significant (p ≥ 0.05). The study underscores the importance of maize adaptive responses in terms of nutrients accumulation and remobilization at different levels of nutrient availability for stabilizing yield.

ACS Style

Krishnendu Ray; Hirak Banerjee; Sudarshan Dutta; Sukamal Sarkar; Timothy Murrell; Vinod K. Singh; Kaushik Majumdar. Macronutrient Management Effects on Nutrient Accumulation, Partitioning, Remobilization, and Yield of Hybrid Maize Cultivars. Frontiers in Plant Science 2020, 11, 1 .

AMA Style

Krishnendu Ray, Hirak Banerjee, Sudarshan Dutta, Sukamal Sarkar, Timothy Murrell, Vinod K. Singh, Kaushik Majumdar. Macronutrient Management Effects on Nutrient Accumulation, Partitioning, Remobilization, and Yield of Hybrid Maize Cultivars. Frontiers in Plant Science. 2020; 11 ():1.

Chicago/Turabian Style

Krishnendu Ray; Hirak Banerjee; Sudarshan Dutta; Sukamal Sarkar; Timothy Murrell; Vinod K. Singh; Kaushik Majumdar. 2020. "Macronutrient Management Effects on Nutrient Accumulation, Partitioning, Remobilization, and Yield of Hybrid Maize Cultivars." Frontiers in Plant Science 11, no. : 1.

Research article
Published: 24 February 2020 in PLOS ONE
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Yield gaps of maize (Zea mays L.) in the smallholder farms of eastern India are outcomes of a complex interplay of climatic variations, soil fertility gradients, socio-economic factors, and differential management intensities. Several machine learning approaches were used in this study to investigate the relative influences of multiple biophysical, socio-economic, and crop management features in determining maize yield variability using several machine learning approaches. Soil fertility status was assessed in 180 farms and paired with the surveyed data on maize yield, socio-economic conditions, and agronomic management. The C&RT relative variable importance plot identified farm size, total labor, soil factors, seed rate, fertilizer, and organic manure as influential factors. Among the three approaches compared for classifying maize yield, the artificial neural network (ANN) yielded the least (25%) misclassification on validation samples. The random forest partial dependence plots revealed a positive association between farm size and maize productivity. Nonlinear support vector machine boundary analysis for the eight top important variables revealed complex interactions underpinning maize yield response. Notably, farm size and total labor synergistically increased maize yield. Future research integrating these algorithms with empirical crop growth models and crop simulation models for ex-ante yield estimations could result in further improvement.

ACS Style

Sudarshan Dutta; Somsubhra Chakraborty; Rupak Goswami; Hirak Banerjee; Kaushik Majumdar; Bin Li; M. L. Jat. Maize yield in smallholder agriculture system—An approach integrating socio-economic and crop management factors. PLOS ONE 2020, 15, e0229100 .

AMA Style

Sudarshan Dutta, Somsubhra Chakraborty, Rupak Goswami, Hirak Banerjee, Kaushik Majumdar, Bin Li, M. L. Jat. Maize yield in smallholder agriculture system—An approach integrating socio-economic and crop management factors. PLOS ONE. 2020; 15 (2):e0229100.

Chicago/Turabian Style

Sudarshan Dutta; Somsubhra Chakraborty; Rupak Goswami; Hirak Banerjee; Kaushik Majumdar; Bin Li; M. L. Jat. 2020. "Maize yield in smallholder agriculture system—An approach integrating socio-economic and crop management factors." PLOS ONE 15, no. 2: e0229100.

Articles
Published: 02 December 2019 in Communications in Soil Science and Plant Analysis
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Eggplant is a preferred vegetable for its nutritional quality and taste. India is the second largest eggplant producer in the world, but the productivity is far below the global average. The present experiment was conducted at the Bidhan Chandra Krishi Viswavidyalaya, West Bengal, India (23°N, 89°E, characteristically Aeric Haplaquept) for consecutive three years to assess the role of selected biofertilizer (Azospirillum, phosphate solubilizing bacteria or PSB) and micronutrient-fertilizer (iron sulfate, zinc sulfate and borax) application in augmenting yield and quality of eggplant (cv. F1-hybrid VNR-60). The experiment was laid out in a thrice replicated factorial randomized block design. Along with regular chemical fertilizers, application of bacterial fertilizers, alone as well as in combination with micronutrients, significantly improved the yield (13.10–15.35 t ha−1) over the control (9.83–12.39 t ha−1). Eggplant yield and quality models developed through artificial neutral network showed that fruit phosphorus (P) concentration was most important factor toward yield prediction followed by zinc (Zn) and soil available iron (Fe) concentration, respectively. Fruit nitrogen (N) concentration showed the highest sensitivity followed by soil available boron (B) and fruit potassium (K) concentration toward protein content. Application of B emerged to be most beneficial along with Azospirillum and PSB in attaining best yield, soil nutrient availabilities and plant nutritional recoveries.

ACS Style

Umalaxmi Thingujam; Kallol Bhattacharyya; Krishnendu Ray; Amit Phonglosa; Arnab Pari; Hirak Banerjee; Sudarshan Dutta; Kaushik Majumdar. Integrated Nutrient Management for Eggplant: Yield and Quality Models through Artificial Neural Network. Communications in Soil Science and Plant Analysis 2019, 51, 70 -85.

AMA Style

Umalaxmi Thingujam, Kallol Bhattacharyya, Krishnendu Ray, Amit Phonglosa, Arnab Pari, Hirak Banerjee, Sudarshan Dutta, Kaushik Majumdar. Integrated Nutrient Management for Eggplant: Yield and Quality Models through Artificial Neural Network. Communications in Soil Science and Plant Analysis. 2019; 51 (1):70-85.

Chicago/Turabian Style

Umalaxmi Thingujam; Kallol Bhattacharyya; Krishnendu Ray; Amit Phonglosa; Arnab Pari; Hirak Banerjee; Sudarshan Dutta; Kaushik Majumdar. 2019. "Integrated Nutrient Management for Eggplant: Yield and Quality Models through Artificial Neural Network." Communications in Soil Science and Plant Analysis 51, no. 1: 70-85.

Research article
Published: 29 May 2019 in PLOS ONE
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In the present two-year study, an attempt was made to estimate the grain yield, grain nutrient uptake, and oil quality of three commonly grown maize (Zea mays L.) hybrids fertilized with varied levels of nitrogen (N), phosphorus (P) and potassium (K). Results obtained from both the experimental years indicated that application of 125% of recommended dose of fertilizer (RDF) recorded maximum grain yield (10.37 t ha-1; 124% higher than control). When compared with 100% RDF, grain yield reduction with nutrient omission was 44% for N omission, 17% for P omission, and 27% for K omission. Nitrogen uptake was increased with increasing NPK levels up to 150% RDF that was statistically at par (p ≥ 0.01) with 125% RDF. Increasing trend in P and K uptake was observed with successive increase in NPK levels up to 125% RDF, above which it declined. The protein content was significantly higher in grains of var. P 3396 with 125% RDF. Nutrient management has significant (p ≤ 0.01) role in the grain oil content. Saturated fatty acids (palmitic, stearic and arachidic acid) content decreased, and unsaturated fatty acid (oleic, linoleic and linolenic acid) increased with increasing NPK levels. The average oleic acid desaturation and linoleic acid desaturation ratios were increased with increasing NPK levels up to 100 and 125% RDF, respectively. However, average monounsaturated fatty acids (MUFA): poly-unsaturated fatty acids (PUFA), saturated: unsaturated as well as linoleic: linolenic acid ratios were increased on receiving 75% RDF, and beyond that it showed decreasing trend. The omission of K had the highest inhibitory effect on corn oil quality followed by N and P omission.

ACS Style

Krishnendu Ray; Hirak Banerjee; Sudarshan Dutta; Alok Kumar Hazra; Kaushik Majumdar. Macronutrients influence yield and oil quality of hybrid maize (Zea mays L.). PLOS ONE 2019, 14, e0216939 .

AMA Style

Krishnendu Ray, Hirak Banerjee, Sudarshan Dutta, Alok Kumar Hazra, Kaushik Majumdar. Macronutrients influence yield and oil quality of hybrid maize (Zea mays L.). PLOS ONE. 2019; 14 (5):e0216939.

Chicago/Turabian Style

Krishnendu Ray; Hirak Banerjee; Sudarshan Dutta; Alok Kumar Hazra; Kaushik Majumdar. 2019. "Macronutrients influence yield and oil quality of hybrid maize (Zea mays L.)." PLOS ONE 14, no. 5: e0216939.

Journal article
Published: 04 December 2018 in Agronomy
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The present study assesses the response of hybrid rice (variety Arize 6444) to potassium (K) application during rainy (wet) seasons of 2016 and 2017 in coastal saline soils of West Bengal, India. The study was conducted at the Regional Research Farm, Bidhan Chandra Krishi Viswavidyalaya, Kakdwip, West Bengal. The soil is clayeywith acidic pH (5.91), saline (Electrical conductivity/EC 1.53 dS m−1) and of high K fertility (366 kg ha−1). The experimental plots were laid out in a randomized complete block design with five (5) K treatments (0, 30, 60, 90, and 120 kg K2O ha−1) with four replications. Plant height, dry matter (DM) in different plant parts, number of tillers, and grain yield were measured in each treatment for the determination of optimum K dose. The study revealed that the stem, leaf, and grain dry matter production at 60 days after transplanting (DAT) and harvest were significantly (p ≤ 0.05) higher at 90 kg K2O ha−1 application. The number of tillers hill−1 was also higher (p ≤ 0.05) in plants fertilized with 90 kg K2O ha−1 over K omission. At harvest, grain K concentration improved (p ≤ 0.05) with K fertilization at 90 kg K2O ha−1, 116% more than the zero-K. Omission of K application from the best treatment (90 kg K2O ha−1) reduced grain yield by 3.5 t ha−1 even though the available K content was high. Potassium uptake restriction due to higher Mg content in the soil may have caused reduced uptake of K leading to yield losses. The present study also showed higher profits with 90 kg K2O ha−1 with higher net returns (US$ 452 ha−1) and benefit:cost ratio (1.75) over other treatments from hybrid rice (var. Arize 6444). From the regression equation, the economic optimum level of K (Kopt) was derived as 101.5 kg K2O ha−1 that could improve productivity of hybrid rice during the wet season in coastal saline soils of West Bengal.

ACS Style

Hirak Banerjee; Krishnendu Ray; Sudarshan Kumar Dutta; Kaushik Majumdar; Talatam Satyanarayana; Jagadish Timsina. Optimizing Potassium Application for Hybrid Rice (Oryza sativa L.) in Coastal Saline Soils of West Bengal, India. Agronomy 2018, 8, 292 .

AMA Style

Hirak Banerjee, Krishnendu Ray, Sudarshan Kumar Dutta, Kaushik Majumdar, Talatam Satyanarayana, Jagadish Timsina. Optimizing Potassium Application for Hybrid Rice (Oryza sativa L.) in Coastal Saline Soils of West Bengal, India. Agronomy. 2018; 8 (12):292.

Chicago/Turabian Style

Hirak Banerjee; Krishnendu Ray; Sudarshan Kumar Dutta; Kaushik Majumdar; Talatam Satyanarayana; Jagadish Timsina. 2018. "Optimizing Potassium Application for Hybrid Rice (Oryza sativa L.) in Coastal Saline Soils of West Bengal, India." Agronomy 8, no. 12: 292.

Journal article
Published: 01 July 2018 in Agricultural Water Management
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Kallol Bhattacharyya; Tanmay Das; Krishnendu Ray; Sudarshan Dutta; Kaushik Majumdar; Arnab Pari; Hirak Banerjee. Yield of and nutrient-water use by maize exposed to moisture stress and K fertilizers in an inceptisol of West Bengal, India. Agricultural Water Management 2018, 206, 31 -41.

AMA Style

Kallol Bhattacharyya, Tanmay Das, Krishnendu Ray, Sudarshan Dutta, Kaushik Majumdar, Arnab Pari, Hirak Banerjee. Yield of and nutrient-water use by maize exposed to moisture stress and K fertilizers in an inceptisol of West Bengal, India. Agricultural Water Management. 2018; 206 ():31-41.

Chicago/Turabian Style

Kallol Bhattacharyya; Tanmay Das; Krishnendu Ray; Sudarshan Dutta; Kaushik Majumdar; Arnab Pari; Hirak Banerjee. 2018. "Yield of and nutrient-water use by maize exposed to moisture stress and K fertilizers in an inceptisol of West Bengal, India." Agricultural Water Management 206, no. : 31-41.

Journal article
Published: 02 October 2017 in Experimental Agriculture
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SUMMARYThe area under hybrid maize cultivation is increasing rapidly across South Asia. However, information regarding the proper nutrient management for modern stay-green maize hybrids in India is not adequate resulting in low productivity. Existing nutrient management practices are not able to capture the momentum change in the scenario of soil nutrient supply capacity and plant nutrient demand for achieving higher yield target. The present study aims at establishing the site-specific nutrient management (SSNM) package for an inceptisol (West Bengal, India). Soil indigenous nutrient supply capacity and nutrient use efficiency was also evaluated by using the nutrient omission plot technique. The experiment was laid out in strip-plot design, assigning three maize hybrids (P 3522, P 3396 and Rajkumar) in the vertical strip and nine fertilizer treatments [50% RDF/Recommended dose of fertilizer, 75% RDF, 100% RDF (200-60-60 kg N-P2O5-K2O ha−1), 125% RDF, 150% RDF, 100% PK, 100% NK, 100% NP and control (zero-NPK)] in the horizontal strip, with three replications. Results of the experiment revealed that the differences among cultivars were generally non-significant. The maize hybrids showed greater yield response to fertilization with N (4.14 Mg ha−1) during winter, followed by K (2.54 Mg ha−1) and P (1.58 Mg ha−1). Indigenous nutrient supply was estimated 107.2, 37.6 and 107.7 kg ha−1 for N, P and K, respectively. Both average agronomic efficiency (AE) and recovery efficiency (RE) were increased with 50% RDF and it decreased with further increase in NPK levels up to 150% RDF. The average internal efficiency (IE) was higher with 50% RDF closely followed by the treatment with absence of N. As grain yields and gross return over fertilizer (GRF) under 75 to 150% NPK treatments were similar, nutrient doses of 150 kg N, 45 kg P2O5 and 45 kg K2O ha−1 were recommended as optimum for maize hybrids.

ACS Style

Krishnendu Ray; Hirak Banerjee; Kallol Bhattacharyya; Sudarshan Dutta; Amit Phonglosa; Arnab Pari; Sukamal Sarkar. SITE-SPECIFIC NUTRIENT MANAGEMENT FOR MAIZE HYBRIDS IN AN INCEPTISOL OF WEST BENGAL, INDIA. Experimental Agriculture 2017, 54, 874 -887.

AMA Style

Krishnendu Ray, Hirak Banerjee, Kallol Bhattacharyya, Sudarshan Dutta, Amit Phonglosa, Arnab Pari, Sukamal Sarkar. SITE-SPECIFIC NUTRIENT MANAGEMENT FOR MAIZE HYBRIDS IN AN INCEPTISOL OF WEST BENGAL, INDIA. Experimental Agriculture. 2017; 54 (6):874-887.

Chicago/Turabian Style

Krishnendu Ray; Hirak Banerjee; Kallol Bhattacharyya; Sudarshan Dutta; Amit Phonglosa; Arnab Pari; Sukamal Sarkar. 2017. "SITE-SPECIFIC NUTRIENT MANAGEMENT FOR MAIZE HYBRIDS IN AN INCEPTISOL OF WEST BENGAL, INDIA." Experimental Agriculture 54, no. 6: 874-887.

Journal article
Published: 17 April 2017 in Archives of Agronomy and Soil Science
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Lalita Rana; Hirak Banerjee; Sudarshan Kumar Dutta; Krishnendu Ray; Kaushik Majumdar; Sukamal Sarkar. Management practices of macronutrients for potato for smallholder farming system at alluvial soil (Entisols) of India. Archives of Agronomy and Soil Science 2017, 63, 1963 -1976.

AMA Style

Lalita Rana, Hirak Banerjee, Sudarshan Kumar Dutta, Krishnendu Ray, Kaushik Majumdar, Sukamal Sarkar. Management practices of macronutrients for potato for smallholder farming system at alluvial soil (Entisols) of India. Archives of Agronomy and Soil Science. 2017; 63 (14):1963-1976.

Chicago/Turabian Style

Lalita Rana; Hirak Banerjee; Sudarshan Kumar Dutta; Krishnendu Ray; Kaushik Majumdar; Sukamal Sarkar. 2017. "Management practices of macronutrients for potato for smallholder farming system at alluvial soil (Entisols) of India." Archives of Agronomy and Soil Science 63, no. 14: 1963-1976.

Journal article
Published: 12 March 2016 in Indian Journal of Plant Physiology
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The present study was carried out during the rabi (winter) season of 2012–2013 and 2013–2014 at Adisaptagram Block Seed Farm, Hooghly, West Bengal to generate information on phenological changes and productivity of potato with varied nitrogen, phosphorus and potassium (NPK) levels. Recommended dose of fertilizer (RDF) application for potato was 200, 150, 150 of N, P2O5, K2O kg ha−1, respectively. The experiment was laid out in randomized block design, having seven treatments, viz., T1 (50 % NPK), T2 (RDF: 100 % NPK), T3 (150 % NPK), T4 (100 % PK, N omission), T5 (100 % NK, P omission); T6 (100 % NP, K omission) and T7 (control, without NPK) with four replications. Results revealed that potato cv. Kufri Jyoti produced higher plant height, number of haulms hill−1 and compound leaves plant−1 when fertilized with higher dose of NPK (150 %), while plants without N produced lower dry weight of above ground biomass because of reduced above growth attributing characters. It appears that dry matter accumulation in potato plant was negatively influenced by N-deficiency and intensive N fertilization. The correlation studies between tuber yield and growth variable showed that the tuber yield was positively correlated with plant height (R2 = 0.97), number of compound leaves per plant (R2 = 0.89), LAI (R2 = 0.88), total dry matter (R2 = 0.89) and tuber bulking rate (R2 = 0.97). Tuber yields under N, P and K deficiencies were 8.46, 25.41 and 26.47 t ha−1, respectively. Result clearly proved that N is the most important nutrient for potato, followed by P and K.

ACS Style

Hirak Banerjee; Lalita Rana; Krishnendu Ray; Sukamal Sarkar; Kallol Bhattacharyya; Sudarshan Dutta. Differential physiological response in potato (Solanum tuberosum L.) upon exposure to nutrient omissions. Indian Journal of Plant Physiology 2016, 21, 129 -136.

AMA Style

Hirak Banerjee, Lalita Rana, Krishnendu Ray, Sukamal Sarkar, Kallol Bhattacharyya, Sudarshan Dutta. Differential physiological response in potato (Solanum tuberosum L.) upon exposure to nutrient omissions. Indian Journal of Plant Physiology. 2016; 21 (2):129-136.

Chicago/Turabian Style

Hirak Banerjee; Lalita Rana; Krishnendu Ray; Sukamal Sarkar; Kallol Bhattacharyya; Sudarshan Dutta. 2016. "Differential physiological response in potato (Solanum tuberosum L.) upon exposure to nutrient omissions." Indian Journal of Plant Physiology 21, no. 2: 129-136.

Book chapter
Published: 23 January 2016 in Biofortification of Food Crops
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Increasing population demands higher production and productivity of crops. Consequently, maintenance of soil fertility is a must for sustainable agriculture and future food security. Agriculturally productive soils have a pool of indigenous nutrients at any given point of time that are stored within the soil and may be available for supporting plant growth. This pool of nutrients, along with nutrient inputs from other sources such as irrigation water, crop residues, etc., constitutes the inherent soil nutrient-supplying capacity. There are several sinks of the native nutrients in the soil, most notably plant removal. Sustenance of inherent fertility of soils depends largely on replenishment of plant nutrients to the soil that are removed through intensive cultivation. Nutrient mining or negative balance between nutrient input and output results when the crop nutrient removal and nutrient losses to other sinks become higher than the soil-inherent nutrient supply. Current nutrient management strategies adopted by most farmers promote nutrient mining, as nutrient applications are inadequate and imbalanced. The application of 4R Nutrient Stewardship Principles, i.e., application of right source of fertilizer at right rate and time through a right method, has the potential to reduce nutrient mining from soils. These core principles help manage nutrients in a manner that crop productivity is sustained or improved without soil fertility depletion, and farm production economics is improved while environmental impact of agricultural nutrients is minimized.

ACS Style

Kaushik Majumdar; Saroj Kumar Sanyal; Sudarshan Kumar Dutta; T. Satyanarayana; V. K. Singh. Nutrient Mining: Addressing the Challenges to Soil Resources and Food Security. Biofortification of Food Crops 2016, 177 -198.

AMA Style

Kaushik Majumdar, Saroj Kumar Sanyal, Sudarshan Kumar Dutta, T. Satyanarayana, V. K. Singh. Nutrient Mining: Addressing the Challenges to Soil Resources and Food Security. Biofortification of Food Crops. 2016; ():177-198.

Chicago/Turabian Style

Kaushik Majumdar; Saroj Kumar Sanyal; Sudarshan Kumar Dutta; T. Satyanarayana; V. K. Singh. 2016. "Nutrient Mining: Addressing the Challenges to Soil Resources and Food Security." Biofortification of Food Crops , no. : 177-198.

Journal article
Published: 19 March 2014 in Crops & Soils
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Sudarshan K. Dutta; Kaushik Majumdar; T. Satyanarayana. India: Nutrient Expert: A precision nutrient management tool for smallholder production systems of India. Crops & Soils 2014, 47, 23 -25.

AMA Style

Sudarshan K. Dutta, Kaushik Majumdar, T. Satyanarayana. India: Nutrient Expert: A precision nutrient management tool for smallholder production systems of India. Crops & Soils. 2014; 47 (2):23-25.

Chicago/Turabian Style

Sudarshan K. Dutta; Kaushik Majumdar; T. Satyanarayana. 2014. "India: Nutrient Expert: A precision nutrient management tool for smallholder production systems of India." Crops & Soils 47, no. 2: 23-25.

Journal article
Published: 30 October 2013 in CSA News
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Sudarshan Dutta; Kaushik Majumdar. Career Transition from University Researchers to Not-for-Profit Extension Scientists. CSA News 2013, 58, 37 -39.

AMA Style

Sudarshan Dutta, Kaushik Majumdar. Career Transition from University Researchers to Not-for-Profit Extension Scientists. CSA News. 2013; 58 (11):37-39.

Chicago/Turabian Style

Sudarshan Dutta; Kaushik Majumdar. 2013. "Career Transition from University Researchers to Not-for-Profit Extension Scientists." CSA News 58, no. 11: 37-39.