FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2795641595> ?p ?o ?g. }

• W2795641595 endingPage "119" @default.
• W2795641595 startingPage "108" @default.
• W2795641595 abstract "Abstract Climate change is recognised to alter the distribution of rainfall and increase temperature and atmospheric CO2 concentration [CO2] and pose a formidable challenge to the sustainability of various cropping industries around the world. Additionally, in specific regions, like China, and for particular crops, like sugarcane, the likely effects of climate change are not straightforward. This is because of non-linearity of the interacting climatic factors on crop growth and yield. In our study, the APSIM-Sugarcane model was used to examine the likely response of sugarcane in future climate scenarios. Statistically downscaled climate data based on 28 global climate models (GCMs) under RCP4.5 and RCP8.5 scenarios were used to generate the change in climate in southern China. The results show that the model well reproduced observations for biomass dry matter (DM), biomass fresh matter (FM), sugar yields (S) and leaf area index (LAI), with values for the index of agreement of 0.65, 0.71, 0.84 and 0.70, respectively. The values of RMSE were relatively low with 7.10 t ha−1 for DM, 18.87 t ha−1 for FM, 0.84 t ha−1 for S and 1.03 m2 m−2 for LAI. On average, the ensemble of downscaled GCM projections showed a small increase in radiation and rainfall in the future at the four locations considered, with significantly increased temperature. Sugarcane yields in southern China appeared to be positively affected under future climate and [CO2] changes. Overall, DM was projected to increase by 5.6 and 6.4 and 6.6 t ha−1 for RCP4.5 in 2030s, 2060s and 2090s relative to 1961–2010, respectively. However, RCP8.5 had less promotion compared to RCP4.5 on DM. Similar increased trends for three future time periods could be found in FM and S. Our results showed that the largest percentage change in S occurred at high latitude locations (e.g., Hezhou), with mean values 28.1% and 39.4% for RCP4.5 and RCP8.5 in 2030s, 44.2% and 23.5% in 2060s, and 41.1% and 45.5% for in 2090s, respectively. In addition, our multiple linear regression analyses showed that the changes in radiation, rainfall and temperature together with elevated [CO2] could explain more than 70% of sugarcane yields change across four locations. Across all locations, increases in sugarcane yields were strongly correlated (P = .001) with each degree (Celsius) increase in future temperature and per mm increase in future rainfall. For example, the DM, FM and S increased 7.8–14.2, 16.6–36.1 and 2.7–6.1 kg ha−1 mm−1 responding to rainfall, respectively. Although uncertainties in our study on the impact of climate change on sugarcane might arise from the choice of crop model and GCMs, the results would be pivotal for developing high-yield adaptive strategies as well as informing policy makers to improve sugarcane productivity in China." @default.
• W2795641595 created "2018-04-13" @default.
• W2795641595 creator A5031245747 @default.
• W2795641595 creator A5040368069 @default.
• W2795641595 creator A5059019659 @default.
• W2795641595 creator A5064128605 @default.
• W2795641595 creator A5069382914 @default.
• W2795641595 creator A5076439335 @default.
• W2795641595 creator A5078016930 @default.
• W2795641595 creator A5081904451 @default.
• W2795641595 date "2018-05-01" @default.
• W2795641595 modified "2023-10-14" @default.
• W2795641595 title "Future climate change projects positive impacts on sugarcane productivity in southern China" @default.
• W2795641595 cites W1968225801 @default.
• W2795641595 cites W1969676767 @default.
• W2795641595 cites W1987895397 @default.
• W2795641595 cites W1989566434 @default.
• W2795641595 cites W1989770155 @default.
• W2795641595 cites W1991737087 @default.
• W2795641595 cites W1992080964 @default.
• W2795641595 cites W2015025809 @default.
• W2795641595 cites W2022283347 @default.
• W2795641595 cites W2024959420 @default.
• W2795641595 cites W2024966118 @default.
• W2795641595 cites W2025971225 @default.
• W2795641595 cites W2028047437 @default.
• W2795641595 cites W2030103530 @default.
• W2795641595 cites W2032330991 @default.
• W2795641595 cites W2036123899 @default.
• W2795641595 cites W2050900916 @default.
• W2795641595 cites W2054102269 @default.
• W2795641595 cites W2068331333 @default.
• W2795641595 cites W2069288653 @default.
• W2795641595 cites W2070971494 @default.
• W2795641595 cites W2074221905 @default.
• W2795641595 cites W2101123072 @default.
• W2795641595 cites W2144422028 @default.
• W2795641595 cites W2147746661 @default.
• W2795641595 cites W2153396739 @default.
• W2795641595 cites W2161436803 @default.
• W2795641595 cites W2167204782 @default.
• W2795641595 cites W222098945 @default.
• W2795641595 cites W2226055900 @default.
• W2795641595 cites W2463290568 @default.
• W2795641595 cites W2503423178 @default.
• W2795641595 cites W2589712349 @default.
• W2795641595 cites W27640898 @default.
• W2795641595 cites W2767829733 @default.
• W2795641595 cites W944162348 @default.
• W2795641595 doi "https://doi.org/10.1016/j.eja.2018.03.007" @default.
• W2795641595 hasPublicationYear "2018" @default.
• W2795641595 type Work @default.
• W2795641595 sameAs 2795641595 @default.
• W2795641595 citedByCount "40" @default.
• W2795641595 countsByYear W27956415952019 @default.
• W2795641595 countsByYear W27956415952020 @default.
• W2795641595 countsByYear W27956415952021 @default.
• W2795641595 countsByYear W27956415952022 @default.
• W2795641595 countsByYear W27956415952023 @default.
• W2795641595 crossrefType "journal-article" @default.
• W2795641595 hasAuthorship W2795641595A5031245747 @default.
• W2795641595 hasAuthorship W2795641595A5040368069 @default.
• W2795641595 hasAuthorship W2795641595A5059019659 @default.
• W2795641595 hasAuthorship W2795641595A5064128605 @default.
• W2795641595 hasAuthorship W2795641595A5069382914 @default.
• W2795641595 hasAuthorship W2795641595A5076439335 @default.
• W2795641595 hasAuthorship W2795641595A5078016930 @default.
• W2795641595 hasAuthorship W2795641595A5081904451 @default.
• W2795641595 hasBestOaLocation W27956415951 @default.
• W2795641595 hasConcept C132651083 @default.
• W2795641595 hasConcept C139719470 @default.
• W2795641595 hasConcept C162324750 @default.
• W2795641595 hasConcept C166957645 @default.
• W2795641595 hasConcept C18903297 @default.
• W2795641595 hasConcept C191935318 @default.
• W2795641595 hasConcept C204983608 @default.
• W2795641595 hasConcept C205649164 @default.
• W2795641595 hasConcept C3017880422 @default.
• W2795641595 hasConcept C39432304 @default.
• W2795641595 hasConcept C48824518 @default.
• W2795641595 hasConcept C54286561 @default.
• W2795641595 hasConcept C6557445 @default.
• W2795641595 hasConcept C86803240 @default.
• W2795641595 hasConceptScore W2795641595C132651083 @default.
• W2795641595 hasConceptScore W2795641595C139719470 @default.
• W2795641595 hasConceptScore W2795641595C162324750 @default.
• W2795641595 hasConceptScore W2795641595C166957645 @default.
• W2795641595 hasConceptScore W2795641595C18903297 @default.
• W2795641595 hasConceptScore W2795641595C191935318 @default.
• W2795641595 hasConceptScore W2795641595C204983608 @default.
• W2795641595 hasConceptScore W2795641595C205649164 @default.
• W2795641595 hasConceptScore W2795641595C3017880422 @default.
• W2795641595 hasConceptScore W2795641595C39432304 @default.
• W2795641595 hasConceptScore W2795641595C48824518 @default.
• W2795641595 hasConceptScore W2795641595C54286561 @default.
• W2795641595 hasConceptScore W2795641595C6557445 @default.
• W2795641595 hasConceptScore W2795641595C86803240 @default.
• W2795641595 hasLocation W27956415951 @default.

• next