Predicting the response of soil potassium to broccoli (Brassica oleracea var. italica) in a Gangetic Inceptisol of West Bengal, India through suitable chemical extractants

2020 ◽  
pp. 1-15
Author(s):  
Shubhadip Dasgupta ◽  
Sudip Sengupta ◽  
Sushanta Saha ◽  
Niharendu Saha ◽  
Kallol Bhattacharyya ◽  
...  
1971 ◽  
Vol 51 (3) ◽  
pp. 197-200 ◽  
Author(s):  
D. C. MUNRO ◽  
J. A. CUTCLIFFE

Brussels sprouts (Brassica oleracea var. gemmifera DC., Jade Cross) require no potassium fertilizer on Prince Edward Island soils if exchangeable soil K as determined by neutral 1 N ammonium acetate exceeds 100 ppm. Below 75 ppm exchangeable soil K, 186 kg K/ha must be applied for maximum yields. Potassium treatments increased yields at only three of 12 locations studied. Leaf tissue potassium concentration was significantly increased at all locations by the fertilizer treatments. Neutral 1 N ammonium acetate for determining exchangeable K was the best soil analysis extract among those tested for measuring available potassium. Tissue analysis gave no information beyond soil analysis for predicting potassium fertilizer requirements on any soil studied.


Planta Medica ◽  
2008 ◽  
Vol 74 (09) ◽  
Author(s):  
BM Silva ◽  
AP Oliveira ◽  
DM Pereira ◽  
C Sousa ◽  
RM Seabra ◽  
...  

Planta Medica ◽  
2007 ◽  
Vol 73 (09) ◽  
Author(s):  
M Gangopadhyay ◽  
R Bhattacharya ◽  
D Chakraborty ◽  
S Bhattacharya ◽  
A Mitra ◽  
...  

2020 ◽  
Vol 12 (1) ◽  
pp. 60-69 ◽  
Author(s):  
Pijush Basak

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.


1949 ◽  
Vol 18 (15) ◽  
pp. 178-179
Author(s):  
Richard L. Park
Keyword(s):  

Sign in / Sign up

Export Citation Format

Share Document