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Not AvailableAgriculture sector is a potential contributor to the total green house gas (GHG) emission with a share of about 24 % (IPCC, AR5 to be released) of the total anthropogenic emission, and a growing global population means that agricultural production will remain high if food demands are to be met. At the same time, there is a huge carbon sink potential in this sector including land use, land-use change, and forestry sector. For over four decades, evidence has been growing that the accumulation of GHGs in the upper atmosphere is leading to changes in climate, particularly increases in temperature. Average global surface temperature increased by 0.6 ± 0.2 °C over the twentieth century and is projected to rise by 0.3–2.5 °C in the next 50 years and 1.4–5.8 °C in the next century (IPCC, Climate change: synthesis report; summary for policymakers. Available: http://www.ipcc.ch/pdf/assessment-report/ar4/syr/ar4_syr_spm.pdf, 2007). In the recent report of IPCC AR5 (yet to be released), it has been observed that warming will continue beyond 2100 under all representative concentration pathways (RCP) scenarios except RCP 2.6. Temperature increase is likely to exceed 1.5 °C relative to 1850–1900 for all RCP scenarios except RCP 2.6. It is likely to exceed 2 °C for RCP 6.0 and RCP 8.5 (Pachauri, Conclusions of the IPCC working group I fifth assessment report, AR4, SREX and SRREN, Warsaw, 11 November 2013). Agriculture is a potential source and sink to GHGs in the atmosphere. It is a source for three primary GHGs: CO2, N2O, and CH4 and sink for atmospheric CO2. The two broad anthropogenic sources of GHG emission from agriculture are the energy use in agriculture (manufacture and use of agricultural inputs and farm machinery) and the management of agricultural land. Mitigation methods to reduce emissions from this sector are thus required, along with identification and quantification of emission sources, so that the agricultural community can act and measure its progress. This chapter focuses on different sources of GHG emission from agriculture sector and their key mitigation strategiesNot Availabl

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Not AvailableThis paper investigates the effects of selected conservation tillage systems compared with conventional tillage after six cropping seasons on soil aggregation, crack parameters and the net loss of water through bypass flow in the Vertisols of central India. The experiment on soybean-wheat cropping system was initiated with soybean crop during kharif 2008 with three tillage treatments namely, (1) no-tillage (NT), (2) reduced tillage (RT) and (3) conventional tillage (CT). After six cropping seasons, the effect of tillage treatments was significant on soil aggregation and crack parameters. The mean weight diameter (MWD) and water stable aggregates (WSA) were significantly higher under NT than CT in the 30 cm soil depth. In the 0–5 cm soil depth, the MWD under CT was 0.59 mm compared to 0.87 mm under NT. However, the conservation tillage practices showed a higher crack width and crack volume and thus caused greater loss of water through bypass flow compared with conventional tillage. The data showed that 43–68% of water applied was lost through bypass flow under NT compared to 26–43% under RT and the least, 20–23% under CT, when computed from below 60 cm soil depth. Thus, the trade-offs, between benefits of conservation tillage practices and the higher loss of water through bypass flow should be taken into account while promoting substitution for conventional tillage in Vertisols of central India.Not Availabl

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Not AvailableAgricultural land degradation due to nutrient deficiencies is a threat to agricultural sustainability. As nutrients availability is influenced by soil heterogeneity, climatic conditions and anthropogenic activities; hence, delineation of nutrient management zones (MZs) based on spatial variability could be an effective management option at regional scale. Thus, the present study was carried out to delineate MZs in the Shiwalik Himalayan region of India by capturing spatial variability of soil properties and secondary and micronutrients status because of the emerging nutrient deficiencies. For the study, a total of 2575 geo‐referenced representative surface (0–15 cm depth) soil samples were collected from the study region covering an area of 53,483 km2. The soils were analysed for pH, electrical conductivity, soil organic carbon, available sulphur (S) and micronutrients (Zn, Fe, Cu, Mn, B and Mo) concentrations. There was a wide variation in soil properties with coefficient of variation values of 14 (for pH) to 86% for available Mo. Geostatistical analysis revealed spherical, Gaussian, exponential, stable, circular and K‐Bessel best‐fit models for soil properties. Most of the soil properties were having moderate spatial dependence except soil pH and S (strong spatial dependence) and Zn (weak spatial dependence). About 49%, 10%, 2%, 13%, 11%, 12% and 8% area of the study region were found to be deficient (including acute and marginal deficiency) in S, Zn, Fe, Cu, Mn, B and Mo, respectively. The principal component analysis and fuzzy c‐mean clustering were performed to develop the MZs. Four principal components with eigenvalues greater than 1 and accounting 65·4% of total variance were retained for further analysis. On the basis of fuzzy performance index and normalized classification entropy, four potential MZs were identified. Analysis of variance confirmed the heterogeneity in most of the studied soil properties among the MZs. The study indicated that the methodology of delineating MZs can be effectively used in site‐specific S and micronutrients management in the Shiwalik Himalayan region of India.Not Availabl