In the present experiment, an effort was made to explore the possibility of utilizing the organic residue i.e. press mud and bagasse byproducts generated from sugar industries to enhance the P uptake by different varieties of wheat. The experiment was conducted with five varieties of wheat (HD 2687, HD 2733, HD 2643, HD 2932 and HD 2894 and three levels of organic residue (a mixture of press mud, bagasse and rice straw in 1:1:1 ratio) i.e. 0, 5 and 10 t/ha. The addition of organic residue had resulted in the production of oxalic acid by the crop. Higher oxalic acid content (9.21 lg/g) was produced by the variety HD 2687 at 60 days after sowing which resulted in the mobilization of immobile soil P and helped in increasing the uptake of P by the crop. The P uptake increased by about 77 % in the treatment that received the organic residue applied @ 10 t/ha over control. It was concluded that organic residue from sugar industries could be used to utilize to mobilize the native soil P to overcome the problem of phosphorus fixation in soils in future.
The performance of gynoecious cucumber (cv. Terminator) was evaluated under three protected structures viz., naturally ventilated polyhouse (NVP), insect proof net house (INH) and shade net house (SNH) at Jodhpur, Rajasthan in hot arid region of India. The photosynthetically active radiation (PAR) inside these structures during cropping period ranged from 154-842 μmol m-2 s-1 which was much lower than the outside. Among structures, air temperature was 1.2°C and 0.7°C lower while relative humidity (RH) was 17 and 4 per cent higher in NVP and SNH respectively as compared to INH. Relatively low air as well as soil temperature, coupled with high RH and optimal radiation in NVP led to better plant growth and physiological activity which resulted in 42 and 142per cent higher yield than INH and SNH, respectively. Hence, it can be recommended that NVP is the best low-tech protected structure which modifies the microclimate favouring successful cultivation of greenhouse cucumber in Indian hot arid regions.
This study used hierarchical cluster analysis (HCA) to delineate the spatial patterns of monthly, seasonal and annual rainfall by clustering 62 stations in the western arid region of India based on a 55 year data set. The statistical properties of clusters were computed and box-whisker plots plotted. Furthermore, the relative influence of three geographical factors (longitude, latitude and altitude) and five statistical parameters (the mean, standard deviation (SD), co-efficient of variation (CV), and maximum and minimum rainfall) on mean rainfall was investigated using principal component analysis (PCA). The use of HCA resulted in four rainfall clusters geographically located at a distinct position. Cluster I, characterized by the lowest mean rainfall and highest CV, was located in the western portion, whereas mean rainfall was the highest for cluster IV situated in the eastern portion. Box-whisker plots revealed a slight skewness, although the monsoon and annual rainfall followed a normal distribution. The PCA results indicted two to three significant principal components (PCs) with eigenvalues > 1. In four clusters, two PCs explained the major variance, ranging from 69.41% (June) to 91.83% (August) in monthly rainfall, from 63.62% (monsoon) to 93.30% (post-monsoon) in seasonal rainfall, and from 71.48% to 90.73% in annual rainfall. In monthly and seasonal rainfall, first PC 1 is termed the "mean rainfall component", which has strong to moderate associations with longitude, and is equally opposed by the CV. These findings are vital for planners and decision-makers to formulate strategies to manage unusual rainwater quantities.
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