Trained neural network to predict paddy yield for various input parameters in Tamil Nadu, India

The major objective of the present study was to explore if Artificial Neural Network (ANN) models with back propagation could efficiently predict the rice yield under various climatic conditions; ground-specific rainfall, ground-specific weather variables and historic yield data. The back propagation algorithm will calculate each expected weight using the error rate as the activity level of a unit was altered.  The errors in the model during the training phase were solved during the back-propagation. The paddy yield prediction took various parameters like rainfall, soil moisture, solar radiation, expected carbon, fertilizers, pesticides, and the long-time paddy yield recorded using Artificial Neural Networks. The R2 value on the test set was found to be 93% and it showed that the model was able to predict the paddy yield better for the given data set. The ANN model was tested with learning rates of 0.25 and 0.5. The number of hidden layers in the first layer was 50 and in the second hidden layer was 30. From this, the testing value of R square was 0.97. The observations with the ANN Model showed that i) the best result for the test set was  R2 value of 0.98, ii) the two hidden layers kept with 50 neurons in the first layer and 30 neurons in the second one, iii) the learning rate was of 0.25. With all these configurations, maximum yield is possible from the paddy crop

Influence of elevated carbon dioxide concentrations on methane emission and its associated soil microflora in rice ecosystem

The dynamics of methane emission and its associated soil microflora in rice ecosystem as a response to elevated CO2 concentrations were studied in open top chamber (OTC) conditions. The treatments consisted of three levels of CO2 (396, 550 and 750 µmol mol-1) and three levels of nitrogen (0, 150 and 200 kg ha-1) and replicated five times in a completely randomized design. The data showed that elevated [CO2] significantly (P ? 0.01) increased the DOC throughout the cropping period with the values ranging from 533 to 722 mg L-1 and 368 to 501 mg L-1 in C750 and Camb, respectively. Methane emission rates were monitored regularly during the experiment period and it was revealed that elevated [CO2] had increased the methane emissions regardless of stages of crop growth.  It was observed that methane emissions were significantly higher under [CO2] of 750 µmol mol-1 by 33 to 54 per cent over the ambient [CO2] of 396 µmol mol-1. Consistent with the observed increases in methane flux, the enumeration of methanogens showed a significant (P ? 0.01) increase under elevated [CO2] with the population ranging from 5.7 to 20.1 x 104 CFU g-1 of dry soil and 5.1 to 16.9 x 104 CFU g-1 of dry soil under C750 and Camb concentrations, respectively. Interestingly, even though higher methanotrophs population was recorded under elevated [CO2], it could not circumvent the methane emission. Overall, the results of OTC studies suggest that methane mitigation strategies need to be explored for the future high CO2 environments.

Oxygen Production and Carbon Capturing Capacity of Various Tree Species in Coimbatore City, India

Climate change, environment pollution, rapid urbanization and industrialization have been recognized as major environmental threats of the present-day scenario. These environmental issues cause severe socio-economic implications across the globe. The living space and human settlements are increasing rapidly in urban areas of India. Simultaneously the existing green cover and tree population are declining in the name of developments. Trees are considered to be one of the important assets in cities, they provide myriad benefits. Considering the importance of trees the cities and their role in reducing the pollution besides adding fresh oxygen to the atmosphere, the present investigation focused with the aim of documenting various tree species in Coimbatore city and to assess their carbon capturing and oxygen release potential. There are about 58 tree species comprising of 27 families, that have been documented and classified into four age classes. Further these tree species were subjected to total biomass, carbon stock, CO2 (eq.), net carbon sequestration and net oxygen release assessment using standard non-destructive method. Among the 58 tree species studied, Albizia lebbeck (2.745 ton tree-1year-1), Tamarindus indica (2.156 ton tree-1year-1), Parkia biglandulosa (1.921 ton tree-1year-1), Delonix regia (1.027 ton tree-1year-1), Kigelia Africana (1.009 ton tree-1year-1), Peltophorum pterocarpum (1.006 ton tree-1year-1), Ficus religiosa (0.906 ton tree-1year-1), Leucaena leucocephala (0.804 ton tree-1year -1) of net oxygen were found to release, Pterospermum acerifolium (0.827 ton tree-1year-1) and Azadirachta indica (0.804 ton tree-1year-1) were found to release high oxygen with more carbon capturing capacity

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Not AvailableSoil carbon sequestration is one of the potential strategies to mitigate the global warming impacts. Despite the fact that the Asian countries with more than 90% of rice fields are serving as a food basket for the global population, they are being vociferously blamed for their contribution towards methane emission and associated climate change. Major part of rice is being cultivated under continuous submergence that may have an influence on active and passive pools of soil carbon besides methane emission. This paper reviews the carbon sequestration potential of rice soils besides discussing the mechanisms and strategies that promote preferential accumulation of soil carbon while minimizing carbon emissions. Overall, the strategies such as practicing the System of Rice Intensification (SRI) method of cultivation, adoption of Integrated Nutrient Management (INM), promoting mycorrhizal symbiosis in aerobic rice system besides enhancement of phytolith occluded carbon are some of the key areas that offers better carbon sequestration in rice ecosystem.Not Availabl

Chemical Synthesis of Sulphur Nanoparticles and Their Characterization

This study focuses on the synthesis and comprehensive characterization of sulphur nanoparticles (S-NPs) using a precipitation method. The synthesis involved sodium thiosulphate and cetyl trimethyl ammonium bromide surfactants in a concentrated hydrochloric acid medium. The resulting S-NPs were thoroughly characterized using various advanced techniques. X-ray diffraction (XRD) analysis confirmed the crystalline nature of the nanoparticles, revealing distinctive diffraction patterns. Transmission electron microscopy (TEM) provided high-resolution images that elucidated the size and morphological aspects of the S-NPs, which exhibited a uniform size distribution. Scanning electron microscopy (SEM) further supported the morphological information, showcasing the surface features of the nanoparticles. Additionally, Fourier-transform infrared spectroscopy (FT-IR) analysis enabled the identification of functional groups and surface chemistry changes associated with the S-NPs. The comprehensive utilization of XRD, TEM, SEM, and FT-IR analysis provides a detailed understanding of the structural, morphological, and chemical attributes of the synthesized sulphur nanoparticles, paving the way for their potential applications in various fields

Synthesis and Characterization of Silica Nanoparticles Derived from Tea Factory Generated Wood Ash

India is the second most prolific tea producing nation in the world, which consumes 82% of its tea production, accounting for 19.5% of global tea consumption. Despite the improvement in technology, employing wood to produce heat has been a vital element of tea processing for generations. Many tea specialists experience that it adds a particular fragrant touch to the finished tea product. However, the management of wood ash generated by tea factories is a significant concern due to the large amount of wood burned during tea processing. Therefore, transportation and effective disposal of these large quantities of wood ash is a great challenge. Hence, this study aimed to effectively transform wood ash into a valuable product, nano silica particles so as to explore the scope for its better utilization in various applications. A series of experiments were carried out to optimize the parameters in the sol-gel technique for synthesizing silica nanoparticles from wood ash. Further, the synthesized nano silica particles were characterized by employing transmission electron microscopy (TEM) and X-ray diffraction (XRD). The standard operational protocol developed through this study demonstrated that wood ash can be effectively converted to silica nanoparticles in the size range of 20-50 nm, spherical in form with crystalline properties. Overall, the results of this work highlights the possibility of utilizing tea factory generated wood ash into silica nanoparticles with an immense potential for varied applications without environmental hazards