Microbial population dynamics under fertigation by distillery effluent in sugarcane-ratoon cropping system

Distillery effluents, a major by-product of distilleries are a major environmental hazard as they are rich in organic matter, micro- and macroelements. Management of this enormous amount of nutrient-rich effluent and its effective utilization is a major challenge. These effluents can be used as a source of nutrient by C₄ crops like sugarcane and subsequent ratoon crops under fertigation system. Impact of fertigation in sugarcane-ratoon cropping system on soil microbial biomass is important as the microbial population plays an important role in the nutrient and biogeochemical recycling. Keeping this in mind, a field experiment was carried out in the sandy loam soil of semi-arid to humid sub-tropical climate of Gajraula (28.85°N, 78.23°E) region, India with different doses of diluted and undiluted effluent for fertigation of sugarcane crop in presence and absence of 50 % recommended dose of fertilizers with suitable replicates. Two post-sown irrigations with four times diluted effluent gave the maximum yield in case of sugarcane crop. Taking into consideration the yield and the culturable microbial population sizes, it can be concluded that one to two post-sown irrigations with diluted effluent can be used to enhance soil fertility in terms of microbial population and to enhance sugarcane and ratoon crop productivity. This package is economically viable and can also take care of distillery waste management and reduction in consumption of chemical fertilizers by 50 %, a key for sustainable agricultural development.     

Reference conditions for rivers of the German Baltic Sea catchment: reconstructing nutrient regimes using the model MONERIS

We introduce an approach for establishing reference conditions (RC) for rivers of the German Baltic Sea catchment, based on predictive modelling. An extensive data set of statistics from the year 1880 was coupled with literature data, providing a comprehensive basis for the calculation of regional historical nutrient emissions into rivers, river nutrient concentrations, and nutrient loading into the sea. Four different scenarios were calculated: scenario 1 assumed RC following previously established criteria for lakes (Poikane et al. in Environ Manag 45(6):1286–1298, 2010), scenario 4 applied the nutrient emission conditions of 1880 (considering non-intensive land usage, the presence of tile drainage systems, sewer systems, and the human population from 1880), and scenarios 2 and 3 considered intermediate conditions. Our results showed that nutrient emissions from scenario 1 accounted for approximately one-tenth of the currently observed total nitrogen (TN) and total phosphorus (TP) emissions. The nutrient emissions calculated for 1880 (scenario 4) were found to be 47 % (TN) and 55 % (TP) higher than those calculated considering reference lake conditions (scenario 1). Our results suggest that RC nutrient concentrations in rivers in the German Baltic Sea catchment were clearly below 0.05 mg/l for TP and 1 mg/l for TN. This range is in accordance with historical and calculated pristine nutrient concentrations from other rivers in similar catchments.     

A conceptual framework for Jatropha seed yield estimation using adaptive neuro-fuzzy inference system (ANFIS) modelling

Jatropha seed yield prediction is one of the most important influencing factors for developing a supply chain modelling of Jatropha seed. The oil from this Jatropha seed is used to blend with diesel to obtain biofuel (Hiromi, Yamamoto, Junichi Fujino, and Kenji Yamaji. 2001. “Evaluation of Bioenergy Potential with a Multi-regional Global-Land-Use-and-Energy Model.” Biomass and Bioenergy 21: 185–203). The Jatropha plant is easy to cultivate and produces high yield if properly maintained. The main focus of this study is to utilize uncultivable wastelands for cultivating Jatropha seeds. As suggested by Liu et al. (Liu, Xiaohong, David B. Grant, Alan C. McKinnon, and Yuanhua Feng. 2010. “An Empirical Examination of the Contribution of Capabilities to the Competitiveness of Logistics Service Providers: A Perspective from China.” International Journal of Physical Distribution & Logistics Management 40 (10): 847–866), the effectiveness of prediction affects the functional characteristics of a supply chain network design. The yield prediction of Jatropha seeds has two important roles which include (i) the identification of external parameters that affects the yield and (ii) the detection of internal attributes that changes the growth characteristics of the Jatropha plant. The development of the fuzzy inference system is characterized by a large number of input variables (Dobrila Petrovic. 2001. International Journal of Production Economics 71: 429–438). A Matlab programming software was used to integrate an adaptive neuro-fuzzy inference system. This approach gave the numerical as well as graphical output that was used to interpret the final result. The root mean square error values were identified for the given inputs which were then compared with the trained input variables to select the best input among the given alternative variables.