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1 Dasgupta, P.; Das, B. S.; Sen, S. K. 2015. Soil water potential and recoverable water stress in drought tolerant and susceptible rice varieties. Agricultural Water Management, 152:110-118. [doi: https://doi.org/10.1016/j.agwat.2014.12.013]
Water stress ; Soil water potential ; Drought tolerance ; Lowland ; Rice ; Plant growth ; Plant developmental stages ; Soil water content ; Crop yield ; Physiological response ; Models / India / Kharagpur
(Location: IWMI HQ Call no: e-copy only Record No: H047497)
(0.73 MB)
We conducted a two-year field experiment to determine if water stress could be exploited to recover yield in one drought resistant (Vandana) and three susceptible (IR36, IR72 and Swarna) rice varieties. Stress was induced in active tillering, flowering and grain filling stages by suspending irrigation until the soil became sufficiently dry and plants began to show stress symptoms when irrigation was resumed, such that plants could recover from stress. We observed that terminal soil water potential (SWP) as low as -110 kPa in the active tillering stage was less detrimental to relative water content, proline content, and electrolyte leakage. A 27% rise in the level of stress led to ~8%, 44% and 21% increase in yield in IR36, Vandana and Swarna. The possible causes are 23%, 39% and 10% increase in the corresponding root biomass ofthe varieties, resulting in higher water uptake in the vegetative stage treatment plots. This was further supported by high correlations between yield and terminal SWP in this treatment. Critical limits of SWP may be identified to exploit the potential of rice varieties to sustain or improve yield under water stress. Results also suggest an opportunity to design a water saving strategy in lowland rice production.
2 Kumar, A.; Nayak, A. K.; Mohanty, S.; Das, B. S.. 2016. Greenhouse gas emission from direct seeded paddy fields under different soil water potentials in eastern India. Agriculture, Ecosystems and Environment, 228:111-123. [doi: https://doi.org/10.1016/j.agee.2016.05.007]
Greenhouse gases ; Carbon dioxide ; Methane ; Nitrous oxide ; Emission reduction ; Direct sowing ; Paddy fields ; Climate change ; Water management ; Water productivity ; Irrigation scheduling ; Strategies ; Crop yield ; Soil properties ; Soil water potential ; Statistical methods / Eastern India / Cuttack
(Location: IWMI HQ Call no: e-copy only Record No: H047868)
(2.46 MB)
In the anticipated water scarcity and global warming scenario; it is imperative to identify suitable irrigation scheduling strategy in paddy fields for increasing water productivity and mitigating greenhouse gas (GHG) emissions. We conducted a two year (dry season of 2014 and 2015) field experiment for irrigation scheduling based on tensiometric measurement of soil water potential (SWP)in order to quantify temporal and seasonal variations in GHGs emissions and their trade off relationship at five levels of SWPs viz. SWP 1 (-20 kPa), SWP 2 (-30 kPa), SWP 3 (-40 kPa), SWP 4 (-50 kPa) and SWP 5 (-60 kPa), in addition to the traditional practice of growing flooded rice (CF). Fluxes of methane (CH4) and nitrous oxide (N2O) during the growing period were measured using manual closed chamber-gas chromatograph and the carbon dioxide (CO2) flux was measured using an infrared CO2 analyzer. A significant decrease in seasonal cumulative CH4 emission (30–60.2%) was recorded at different SWPs as compared to CF. In contrast, emission of CO2 and N2O increased by 12.9–26.6% and 16.3–22.1% respectively at SWPs 1 and 2; conversely, a significant decrease in emissions of these gases were observed at higher SWPs (SWPs 3–5). Among different SWP treatments, irrigation scheduling at SWP 2 maintained yield at par with CF with water saving of 32.9–41.1% and reduced CH4 emission (43–44.1%). However, due to increase in CO2 and N2O emission at SWP 2, there was no significant reduction in global warming potential (GWP) as compared with CF. Among different rice growth stages GHGs emission were predominant during vegetative growth stage. Regression relationship of GHGs emission with key soil parameters was employed to predict seasonal emissions of GHGs from paddy field. The results of this study suggest that scheduling irrigation at SWP 2 can be an effective strategy in order to save water, maintain rice yield and mitigate CH4 emission from direct seeded paddy fields in eastern India, however further research is needed to identify suitable management strategy for reducing CO2 and N2O emissions at SWP 2 in order to reduce the GWP.
3 Mishra, D.; Das, B. S.; Sinha, T.; Hoque, J. M.; Reynolds, C.; Islam, M. R.; Hossain, M.; Sar, P.; Menon, M. 2021. Living with arsenic in the environment: an examination of current awareness of farmers in the Bengal Basin using hybrid feature selection and machine learning. Environment International, 153:106529. (Online first) [doi: https://doi.org/10.1016/j.envint.2021.106529]
Drinking water ; Arsenic ; Contamination ; Awareness ; Farmers ; Farming systems ; Communities ; Socioeconomic environment ; Water supply ; Irrigation ; Public health ; Policies ; Machine learning ; Models / Bangladesh / India / Bengal Basin / West Bengal
(Location: IWMI HQ Call no: e-copy only Record No: H050292)
https://www.sciencedirect.com/science/article/pii/S0160412021001549/pdfft?md5=3520f677cef94fd26d81d0009caa2d29&pid=1-s2.0-S0160412021001549-main.pdf
https://vlibrary.iwmi.org/pdf/H050292.pdf
https://vlibrary.iwmi.org/pdf/H050292.pdf
(2.07 MB) (2.07 MB)
High levels of arsenic in drinking water and food materials continue to pose a global health challenge. Over 127 million people alone in Bangladesh (BD) and West Bengal (WB) state of India are exposed to elevated levels of arsenic in drinking water. Despite decades of research and outreach, arsenic awareness in communities continue to be low. Specifically, very few studies reported arsenic awareness among low-income farming communities. A comprehensive approach to assess arsenic awareness is a key step in identifying research and development priorities so that appropriate stakeholder engagement may be designed to tackle arsenic menace. In this study, we developed a comprehensive arsenic awareness index (CAAI) and identified key awareness drivers (KADs) of arsenic to help evaluate farmers’ preferences in dealing with arsenic in the environment. The CAAI and KADs were developed using a questionnaire survey in conjunction with ten machine learning (ML) models coupled with a hybrid feature selection approach. Two questionnaire surveys comprising of 73 questions covering health, water and community, and food were conducted in arsenic-affected areas of WB and BD. Comparison of CAAIs showed that the BD farmers were generally more arsenic-aware (CAAI = 7.7) than WB farmers (CAAI = 6.8). Interestingly, the reverse was true for the awareness linked to arsenic in the food chain. Application of hybrid feature selection identified 15 KADs, which included factors related to stakeholder interventions and cropping practices instead of commonly perceived factors such as age, gender and income. Among ML algorithms, classification and regression trees and single C5.0 tree could estimate CAAIs with an average accuracy of 84%. Both communities agreed on policy changes on water testing and clean water supply. The CAAI and KADs combination revealed a contrasting arsenic awareness between the two farming communities, albeit their cultural similarities. Specifically, our study shows the need for increasing awareness of risks through the food chain in BD, whereas awareness campaigns should be strengthened to raise overall awareness in WB possibly through media channels as deemed effective in BD.
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