scholarly journals Pattern of Green Leafhopper Infestation in Boro Rice in Tarai Region of West Bengal Using Distributional and Modular Approach

2018 ◽  
Vol 7 (09) ◽  
pp. 1020-1026
Author(s):  
Pramit Pandit ◽  
K.N. Krishnamurthy ◽  
Bishvajit Bakshi ◽  
Prithwiraj Dey ◽  
Nripendra Laskar
Keyword(s):  
West Bengal ◽  
Modular Approach ◽  
Green Leafhopper ◽  
Boro Rice

scholarly journals Yield of Boro Rice as Influenced by Integrated Nutrient Management in Lateritic Soils of West Bengal

2019 ◽  
Vol 8 (01) ◽  
pp. 1743-1754
Author(s):  
Monisankar Bera ◽  
Goutam K. Ghosh ◽  
Suchhanda Mondal ◽  
Pabitra K. Biswas ◽  
Manik C. Kundu
Keyword(s):  
Nutrient Management ◽  
West Bengal ◽  
Integrated Nutrient Management ◽  
Lateritic Soils ◽  
Boro Rice

scholarly journals Effect of Seaweeds on Growth and Yield of Boro Rice (Oryza sativa L.)

2020 ◽  
pp. 28-34
Author(s):  
Madhusri Pramanik ◽  
Dhananjoy Dutta ◽  
Indranil Samui
Keyword(s):  
West Bengal ◽  
Foliar Application ◽  
Oryza Sativa L ◽  
Block Design ◽  
Foliar Spray ◽  
Seaweed Extract ◽  
Growth And Yield ◽  
Cost Ratio ◽  
Residual Soil ◽  
Boro Rice

Introduction: Seaweed extract, an organic bio-stimulant has emerged as a promising tool for increasing crop growth and yield without affecting soil health and environment. Aim: i) To study the efficacy of seaweed extract on growth and yield of boro rice ii) To evaluate the nutrients uptake and residual soil fertility under different treatments iii)To assess the economic viability of using the bio-stimulants in rice production. Study Design:  Seven treatments were laid out inrandomized block design with three replications. Place and Duration of the Study: Boro seasons of 2016-17 and 2017-18 at Instructional Farm of BCKV, Nadia, under new alluvial zone of West Bengal. Methods: Field experiment was carried out in boro (summer) rice (cv. Satabdi) with seven treatments viz., T1-100% RDF (120:60:60 kg/ha N, P2O5 and K2O), T2-100% RDF+ biozyme liquid @ 2.5ml/l of water (seed soaking), T3-100% RDF + biozyme liquid @ 10ml/l of water (root dipping), T4- 100% RDF+ biozyme granule @15 kg/ha (soil application at 15 and 45 DAT)+ liquid @ 625 ml/ha (foliar spray at 15 and 45 DAT), T5-75% RDF + biozyme liquid, T6-75% RDF+ biozyme granule+ liquid  and T7-75% RDF+ amaze-X granule @ 10kg/ha at 45 DAT + biozymegranule + liquid. Results: Results revealed that the maximum grain yield (4.88 t/ ha) was obtained under T7 followed by T4 and T6, however, the net return (Rs.25576/ha) and benefit-cost ratio (1.51) of T6 treatment gave maximum. Conclusion: It may be concluded that T7 treatment performed best in terms of growth and yield of Boro rice but T6 treatment gave the highest B:C ratio and net income which is supposed to be more economical to the small and marginal farmers. Therefore, integrated use of 75% RDF and biozyme soil & foliar application can be recommended for boro rice under new alluvial zone of West Bengal.

An investigation on in vitro propagation of Colchicum luteum and its evaluation of colchicine for the economic benefit of rural people in West Bengal

Planta Medica ◽  
2007 ◽  
Vol 73 (09) ◽  
Author(s):  
M Gangopadhyay ◽  
R Bhattacharya ◽  
D Chakraborty ◽  
S Bhattacharya ◽  
A Mitra ◽  
...  
Keyword(s):  
Economic Benefit ◽  
In Vitro Propagation ◽  
West Bengal ◽  
Rural People

Forecasting of Summer Monsoon Rainfall over Gangetic West Bengal, India Utilising Intrinsic Mode Functions, Linear and Neural Regression

2020 ◽  
Vol 12 (1) ◽  
pp. 60-69 ◽  
Author(s):  
Pijush Basak
Keyword(s):  
Neural Network ◽  
West Bengal ◽  
Monsoon Rainfall ◽  
Linear Part ◽  
Intrinsic Mode Functions ◽  
Quasi Biennial Oscillation ◽  
Nonlinear Part ◽  
South West ◽  
South West Monsoon ◽  
West Monsoon

The South West Monsoon rainfall data of the meteorological subdivision number 6 of India enclosing Gangetic West Bengal is shown to be decomposable into eight empirical time series, namely Intrinsic Mode Functions. This leads one to identify the first empirical mode as a nonlinear part and the remaining modes as the linear part of the data. The nonlinear part is modeled with the technique Neural Network based Generalized Regression Neural Network model technique whereas the linear part is sensibly modeled through simple regression method. The different Intrinsic modes as verified are well connected with relevant atmospheric features, namely, El Nino, Quasi-biennial Oscillation, Sunspot cycle and others. It is observed that the proposed model explains around 75% of inter annual variability (IAV) of the rainfall series of Gangetic West Bengal. The model is efficient in statistical forecasting of South West Monsoon rainfall in the region as verified from independent part of the real data. The statistical forecasts of SWM rainfall for GWB for the years 2012 and 2013 are108.71 cm and 126.21 cm respectively, where as corresponding to the actual rainfall of 93.19 cm 115.20 cm respectively which are within one standard deviation of mean rainfall.

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