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Anand, India

Anand Agricultural University is located in the western Indian state of Gujarat between the cities of Vadodara and Ahmedabad. This was formerly the Anand Campus of Gujarat Agricultural University, which is now independent. It has three constituent colleges, for agriculture, veterinary science and animal husbandry and dairy science. The jurisdiction of the university covers Kheda, Anand, Ahmedabad, Vadodara, Dahod and Panchmahal districts. It was set up to provide education support to the farming community in areas such as Agriculture, Horticulture, Engineering, Information technology and Business Studies. The university aims to promote development in rural areas through education, research and support services. Wikipedia.

Raul S.K.,Anand Agricultural University | Panda S.N.,Indian Institute of Technology Kharagpur
Water Resources Management | Year: 2013

The canal water supply, which is the only source of irrigation, in the rice-dominated cropping system of the Hirakud canal command (eastern India) is able to meet only 54 % of the irrigation demand at 90 % probability of exceedance. Hence, considering groundwater as the supplemental source of irrigation, conjunctive use management study by combined simulation-optimization modelling was undertaken in order to predict the maximum permissible groundwater pumpage from the command area. Further, optimal land and water resources allocation model was developed to determine the optimal cropping pattern for maximizing net annual return. The modelling results suggested that 2. 0 and 2. 3 million m3 of groundwater can be pumped from the bottom aquifer during monsoon and non-monsoon seasons, respectively, at 90 % probability of exceedance of rainfall and canal water availability (PERC). Optimal cropping patterns and pumping strategies can lead to about 51. 3-12. 5 % increase in net annual return from the area at 10-90 % PERC. The sensitivity analysis of the model indicates that the variation in the market price of crops has very high influence on the optimal solution followed by the cost of cultivation and cultivable area. Finally, different future scenarios of land and water use were formulated for the command area. The adoption of optimal cropping patterns and optimal pumping strategies is strongly recommended for sustainable management of available land and water resources of the canal command under hydrological uncertainties. © 2013 Springer Science+Business Media Dordrecht. Source

Patel L.,Gujarat University | Thaker A.,Anand Agricultural University
Renal Failure | Year: 2014

Diabetic nephropathy (DN) is the most common cause of end-stage renal disease worldwide. The pathophysiologic mechanisms of diabetic nephropathy are incompletely understood but include overproduction of various growth factors and cytokines. Upregulation of vascular endothelial growth factor (VEGF) is a pathogenic event occurring in most forms of podocytopathy; however, the mechanisms that regulate this growth factor induction are not clearly identified. A2B receptors have been found to regulate VEGF expression under hypoxic environment in different tissues. One proposed hypothesis in mediating diabetic nephropathy is the modulation of VEGF-NO balance in renal tissue. We determined the role of adenosine A2B receptor in mediating VEGF overproduction and nitrite in diabetic nephropathy. The renal content of A2B receptors and VEGF was increased after 8 weeks of diabetes induction. The renal and plasma nitrite levels were also reduced in these animals. In vivo administration of A2B adenosine receptor antagonist (MRS1754) inhibited the renal over expression of VEGF and adverse renal function parameters. The antagonist administration also improved the kidney tissue nitrite levels. In conclusion, we demonstrated that VEGF induction via adenosine signaling might be the critical event in regulating VEGF-NO axis in diabetic nephropathy. © 2014 Informa Healthcare USA, Inc. Source

Singh B.P.,National Dairy Research Institute | Vij S.,National Dairy Research Institute | Hati S.,Anand Agricultural University
Peptides | Year: 2014

Biologically active peptides play an important role in metabolic regulation and modulation. Several studies have shown that during gastrointestinal digestion, food processing and microbial proteolysis of various animals and plant proteins, small peptides can be released which possess biofunctional properties. These peptides are to prove potential health-enhancing nutraceutical for food and pharmaceutical applications. The beneficial health effects of bioactive peptides may be several like antihypertensive, antioxidative, antiobesity, immunomodulatory, antidiabetic, hypocholesterolemic and anticancer. Soybeans, one of the most abundant plant sources of dietary protein, contain 36-56% of protein. Recent studies showed that soy milk, an aqueous extract of soybean, and its fermented product have great biological properties and are a good source of bioactive peptides. This review focuses on bioactive peptides derived from soybean; we illustrate their production and biofunctional attributes. © 2014 Elsevier Inc. Source

Tiwari M.K.,Anand Agricultural University | Adamowski J.,McGill University
Water Resources Research | Year: 2013

A new hybrid wavelet-bootstrap-neural network (WBNN) model is proposed in this study for short term (1, 3, and 5 day; 1 and 2 week; and 1 and 2 month) urban water demand forecasting. The new method was tested using data from the city of Montreal in Canada. The performance of the WBNN method was compared with the autoregressive integrated moving average (ARIMA) and autoregressive integrated moving average model with exogenous input variables (ARIMAX), traditional NNs, wavelet analysis-based NNs (WNN), bootstrap-based NNs (BNN), and a simple naïve persistence index model. The WBNN model was developed as an ensemble of several NNs built using bootstrap resamples of wavelet subtime series instead of raw data sets. The results demonstrated that the hybrid WBNN and WNN models produced significantly more accurate forecasting results than the traditional NN, BNN, ARIMA, and ARIMAX models. It was also found that the WBNN model reduces the uncertainty associated with the forecasts, and the performance of WBNN forecasted confidence bands was found to be more accurate and reliable than BNN forecasted confidence bands. It was found in this study that maximum temperature and total precipitation improved the accuracy of water demand forecasts using wavelet analysis. The performance of WBNN models was also compared for different numbers of bootstrap resamples (i.e., 25, 50, 100, 200, and 500) and it was found that WBNN models produced optimum results with different numbers of bootstrap resamples for different lead time forecasts with considerable variability. Key Points Comparison of different methods for urban water demand forecasting Wavelet-bootstrap-neural network method is found accurate and reliable. Significance of input variables on forecasting performance. ©2013. American Geophysical Union. All Rights Reserved. Source

The performance of birds appears to vary among the flock of growing broilers which may in part be due to variation in their gut microbiota. In the view of poultry industry, it is desirable to minimise such variation. We investigated metagenomic profile of fecal bacteria in birds with high and low feed conversion ratio (FCR) to identify microbial community linked to low and high FCR by employing high throughput pyrosequencing of 16S rRNA genomic targets. Therefore feeding trial was investigated in order to identify fecal bacteria consistently linked with better feed conversion ratio in bird performance as measured by body weight gain. High-throughput 16S rRNA gene based pyrosequencing was used to provide a comparative analysis of fecal microbial diversity. The fecal microbial community of birds was predominated by Proteobacteria (48.04 % in high FCR and 49.98 % in low FCR), Firmicutes (26.17 % in high FCR and 36.23 % in low FCR), Bacteroidetes (18.62 % in high FCR and 11.66 % in low FCR), as well as unclassified bacteria (15.77 % in high FCR and 14.29 % in low FCR), suggesting that a large portion of fecal microbiota is novel and could be involved in currently unknown functions. The most prevalent bacterial classes in high FCR and low FCR were Gammaproteobacteria, Clostridia and Bacteroidia. However in low FCR birds Phascolarctobacterium, Faecalibacterium and Clostridium predominated among the Clostridia. In FCR comparison of fecal bacteria, about 36 genera were differentially abundant between high and low FCR birds. This information could be used to formulate effective strategies to improve feed efficiency and feed formulation for optimal gut health. Source

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