FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2767739997> ?p ?o ?g. }

• W2767739997 endingPage "33" @default.
• W2767739997 startingPage "24" @default.
• W2767739997 abstract "Excessive water and fertilizer inputs have led to a series of environmental problems in vegetable production areas in China. Identifying the fates of water and nutrients is crucial to develop best management strategies in intensive vegetable production systems. The objectives of this study were to (i) develop a scientific water and nitrogen (N) management tool for intensive greenhouse vegetable production in China, and (ii) evaluate the model performance in the simulating the fate of water and N, and vegetable growth under different water and N management practices in China. A vegetable growth component was added to the field soil-crop system model WHCNS (soil Water Heat Carbon Nitrogen Simulator), named WHCNS_Veg. Parameters for the model were estimated and a sensitivity analysis was conducted by coupling the model with the model-independent parameter estimation program (PEST). Data used to test the model came from two years of cucumber and tomato experiments with various water and N combinations in Shandong province, China. The results of sensitivity analysis showed that the soil hydraulic parameters and vegetable genetic parameters had a relatively higher sensitivity compared with those of N transformation parameters. The saturated soil water content had the highest sensitivity among soil hydraulic parameters, and the total available accumulated temperature, crop coefficient and maximum root depth had higher sensitivity for both vegetable crops. Among the N transformation parameters, the parameters related to nitrification had the highest sensitivity. The automatic optimization algorithm performed well in adjusting soil hydraulic parameters, vegetable genetic parameters and N transformation parameters. The normalized root mean square error for soil water content, soil nitrate concentration, marketable fresh yield and vegetable N uptake were 5.7%, 28.0%, 2.7% and 8.3%, respectively, and indices of agreement were 0.727, 0.730, 0.997 and 0.832, respectively. The results indicated that the WHCNS_Veg model has great potential to simulate and analyze water and N fates, and vegetable growth for the intensive greenhouse vegetable production in China." @default.
• W2767739997 created "2017-11-17" @default.
• W2767739997 creator A5051761403 @default.
• W2767739997 creator A5066014894 @default.
• W2767739997 creator A5067468840 @default.
• W2767739997 creator A5077901649 @default.
• W2767739997 creator A5090377661 @default.
• W2767739997 date "2018-01-01" @default.
• W2767739997 modified "2023-10-16" @default.
• W2767739997 title "Developing a water and nitrogen management model for greenhouse vegetable production in China: Sensitivity analysis and evaluation" @default.
• W2767739997 cites W1801238872 @default.
• W2767739997 cites W1935131971 @default.
• W2767739997 cites W1970478569 @default.
• W2767739997 cites W1972034227 @default.
• W2767739997 cites W1974727985 @default.
• W2767739997 cites W1975191127 @default.
• W2767739997 cites W1979325376 @default.
• W2767739997 cites W1984886861 @default.
• W2767739997 cites W1987259321 @default.
• W2767739997 cites W1990674308 @default.
• W2767739997 cites W1991609690 @default.
• W2767739997 cites W2019022785 @default.
• W2767739997 cites W2021963942 @default.
• W2767739997 cites W2024400993 @default.
• W2767739997 cites W2024618316 @default.
• W2767739997 cites W2030885431 @default.
• W2767739997 cites W2034373477 @default.
• W2767739997 cites W2043150661 @default.
• W2767739997 cites W2047884674 @default.
• W2767739997 cites W2055687699 @default.
• W2767739997 cites W2068166506 @default.
• W2767739997 cites W2069399571 @default.
• W2767739997 cites W2069670567 @default.
• W2767739997 cites W2083442576 @default.
• W2767739997 cites W2087070363 @default.
• W2767739997 cites W2102648957 @default.
• W2767739997 cites W2134463989 @default.
• W2767739997 cites W2152200181 @default.
• W2767739997 cites W2218665055 @default.
• W2767739997 cites W2281297709 @default.
• W2767739997 cites W2345524994 @default.
• W2767739997 cites W2407334310 @default.
• W2767739997 cites W2413360889 @default.
• W2767739997 cites W2521765710 @default.
• W2767739997 cites W2589633489 @default.
• W2767739997 cites W288263789 @default.
• W2767739997 doi "https://doi.org/10.1016/j.ecolmodel.2017.10.016" @default.
• W2767739997 hasPublicationYear "2018" @default.
• W2767739997 type Work @default.
• W2767739997 sameAs 2767739997 @default.
• W2767739997 citedByCount "31" @default.
• W2767739997 countsByYear W27677399972018 @default.
• W2767739997 countsByYear W27677399972019 @default.
• W2767739997 countsByYear W27677399972020 @default.
• W2767739997 countsByYear W27677399972021 @default.
• W2767739997 countsByYear W27677399972022 @default.
• W2767739997 countsByYear W27677399972023 @default.
• W2767739997 crossrefType "journal-article" @default.
• W2767739997 hasAuthorship W2767739997A5051761403 @default.
• W2767739997 hasAuthorship W2767739997A5066014894 @default.
• W2767739997 hasAuthorship W2767739997A5067468840 @default.
• W2767739997 hasAuthorship W2767739997A5077901649 @default.
• W2767739997 hasAuthorship W2767739997A5090377661 @default.
• W2767739997 hasConcept C105462344 @default.
• W2767739997 hasConcept C127413603 @default.
• W2767739997 hasConcept C142796444 @default.
• W2767739997 hasConcept C159390177 @default.
• W2767739997 hasConcept C159750122 @default.
• W2767739997 hasConcept C18903297 @default.
• W2767739997 hasConcept C21200559 @default.
• W2767739997 hasConcept C24326235 @default.
• W2767739997 hasConcept C2780560099 @default.
• W2767739997 hasConcept C32198211 @default.
• W2767739997 hasConcept C39432304 @default.
• W2767739997 hasConcept C6557445 @default.
• W2767739997 hasConcept C86803240 @default.
• W2767739997 hasConcept C88463610 @default.
• W2767739997 hasConceptScore W2767739997C105462344 @default.
• W2767739997 hasConceptScore W2767739997C127413603 @default.
• W2767739997 hasConceptScore W2767739997C142796444 @default.
• W2767739997 hasConceptScore W2767739997C159390177 @default.
• W2767739997 hasConceptScore W2767739997C159750122 @default.
• W2767739997 hasConceptScore W2767739997C18903297 @default.
• W2767739997 hasConceptScore W2767739997C21200559 @default.
• W2767739997 hasConceptScore W2767739997C24326235 @default.
• W2767739997 hasConceptScore W2767739997C2780560099 @default.
• W2767739997 hasConceptScore W2767739997C32198211 @default.
• W2767739997 hasConceptScore W2767739997C39432304 @default.
• W2767739997 hasConceptScore W2767739997C6557445 @default.
• W2767739997 hasConceptScore W2767739997C86803240 @default.
• W2767739997 hasConceptScore W2767739997C88463610 @default.
• W2767739997 hasLocation W27677399971 @default.
• W2767739997 hasOpenAccess W2767739997 @default.
• W2767739997 hasPrimaryLocation W27677399971 @default.
• W2767739997 hasRelatedWork W2085776588 @default.
• W2767739997 hasRelatedWork W2151725496 @default.
• W2767739997 hasRelatedWork W2155750121 @default.
• W2767739997 hasRelatedWork W2359161550 @default.

• next