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dc.contributorDevkota Wasti, Minaen_US
dc.contributorPaudel, Gokul Prasaden_US
dc.contributorJames McDonald, Andrewen_US
dc.creatorDevkota, Krishna Prasaden_US
dc.date.accessioned2021-07-01T17:45:57Z
dc.date.available2021-07-01T17:45:57Z
dc.identifierhttps://mel.cgiar.org/dspace/limiteden_US
dc.identifier.citationKrishna Prasad Devkota, Mina Devkota Wasti, Gokul Prasad Paudel, Andrew James McDonald. (25/5/2021). Coupling landscape-scale diagnostics surveys, on-farm experiments, and simulation to identify entry points for sustainably closing rice yield gaps in Nepal. Agricultural Systems, 192, pp. 1-13.en_US
dc.identifier.urihttps://hdl.handle.net/20.500.11766/13305
dc.description.abstractCONTEXT Rice is the primary staple food crop in Nepal, contributing 20% of the agricultural gross domestic product and more than 50% of the total calories in the national diet. Nevertheless, the productivity of rice (3.36 t ha−1) is the lowest in South Asia region. OBJECTIVE The objective of this study was to employ a mixed-methods approach to characterize and decompose yield gaps (YGs) in the context of identifying sustainable intensification pathways for rice production in Nepal. METHODS Methodologies include: a) landscape-scale crop diagnostic survey on crop management, field attributes, and productivity outcomes combined with gridded soil and daily weather data to decompose rice yield gaps into constituent factors with machine learning diagnostics; b) with survey data, computation of key performance indicators to identify factors associated with productivity, profitability, and resource use efficiencies; c) complementary multi-location on-farm experiments (2011–2017) evaluating new agronomic management practices; and d) dynamic simulation (ORYZA3) to derive estimates of rice yield potential. RESULTS AND CONCLUSIONS Analysis of survey data suggests an exploitable YG of 2.57 t ha−1 (40%) and the total YG of 4.85 t ha−1 (55%) indicating substantial scope for increasing rice yields in Nepal. Frequency of irrigation, amount of late-season rainfall, soil type, amount of early-season rainfall, presence of water stress, soil pH, and nitrogen (N) and phosphorus (P) fertilizer rates are the principal determinants of productivity outcomes in descending ranked order. Efficiency metrics suggest rice farmers in the study region make good use of fertilizer inputs, but since application rates are very low (e.g. most farmers apply <20 kg P ha−1) unsustainable mining of soil nutrients is likely common. Farmers in the top 10% of the yield distribution had lower greenhouse gas emission intensities (−43%), increased water productivity (+66%), and higher use efficiencies of N and P fertilizers (+28% and + 20%, respectively), suggesting that yield intensification can be achieved without tradeoffs with key environmental performance indicators. On-farm experiments conducted over several seasons support insights from surveys by demonstrating that major gains in rice yield (1.86 t ha−1) and profitability (US$ 243 ha−1) are achievable through the adoption of good agronomic practices. SIGNIFICANCE Through a mixed methods approach, our results suggest that adoption of integrated 'good agronomic practices' can close YGs and improve food security outcomes associated with the rice-based agricultural systems of Nepal while simultaneously preserving or enhancing key sustainability and livelihood objectives.en_US
dc.formatPDFen_US
dc.languageenen_US
dc.publisherElsevier Massonen_US
dc.sourceAgricultural Systems;192,(2021) Pagination 1-13en_US
dc.subjectsustainability indicatorsen_US
dc.subjectgood agronomic practicesen_US
dc.titleCoupling landscape-scale diagnostics surveys, on-farm experiments, and simulation to identify entry points for sustainably closing rice yield gaps in Nepalen_US
dc.typeJournal Articleen_US
dcterms.available2021-05-25en_US
dcterms.extent1-13en_US
cg.creator.idDevkota Wasti, Mina: 0000-0002-2348-4816en_US
cg.subject.agrovocsustainable intensificationen_US
cg.subject.agrovocyield gapen_US
cg.subject.agrovocmachine learningen_US
cg.contributor.centerInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.contributor.centerInternational Maize and Wheat Improvement Center - CIMMYTen_US
cg.contributor.centerCornell University - CORNELLen_US
cg.contributor.centerMohammed VI Polytechnic University - UM6Pen_US
cg.contributor.crpCGIAR Research Program on Wheat - WHEATen_US
cg.contributor.funderInternational Maize and Wheat Improvement Center - CIMMYTen_US
cg.contributor.projectCRP WHEAT Phase IIen_US
cg.contributor.project-lead-instituteInternational Center for Agricultural Research in the Dry Areas - ICARDAen_US
cg.date.embargo-end-dateTimelessen_US
cg.coverage.regionSouthern Asiaen_US
cg.coverage.countryNPen_US
cg.contactkrishna.devkota@um6p.maen_US
cg.identifier.doihttps://dx.doi.org/10.1016/j.agsy.2021.103182en_US
cg.isijournalISI Journalen_US
dc.identifier.statusTimeless limited accessen_US
mel.impact-factor5.370en_US
cg.issn0308-521Xen_US
cg.journalAgricultural Systemsen_US
cg.volume192en_US


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