In order to explore the applicability of the peanut growth simulation model CSM-CROPGRO-Peanut under conditions of mulched drip irrigation in Xinjiang, and to determine the optimal scenario for parameter estimation and model validation, field experiments were conducted in 2022 and 2023 on the water and nitrogen regulation of peanut. Based on the water requirements during the stages of peanut growth, three irrigation levels (low, medium, and high) and two nitrogen application levels (100% N and 50% N) were set, resulting in six treatments. An additional control treatment (CK) with a medium irrigation level and no nitrogen application was also included. In this study, four different parameter estimation and validation protocols were designed, and different parameter estimation results were obtained using the DSSAT-GLUE parameter estimation module. The results showed that the FL-SH (time between first flower and first pod), FL-SD (time between first flower and first seed), SIZLF (time between first flower and first seed), XFRT (maximum size of full leaf), and WTPSD (maximum weight per seed) parameters exhibited strong variability, with coefficients of variation of 24.33%, 22.9%, 19.78%, 14.47%, and 23.82%, respectively, and were significantly affected by environment-management interactions. Other parameters showed weaker variability, with coefficients of variation that were all less than 10%. The model outputs varied significantly among different parameter estimation protocols. Scenario 3, which used data from the adequate irrigation and adequate fertilization treatment (W3N2) environment across both years for parameter estimation and data from other treatments for validation, showed the highest model calibration and validation accuracy. The average absolute relative error (ARE) and normalized root mean square error (nRMSE) for model calibration and validation were the lowest at 9.1% and 10.1%, respectively. The CSM-CROPGRO-Peanut model effectively simulated peanut growth and development as well as soil moisture dynamics under mulched drip irrigation conditions in Xinjiang, with the highest simulation accuracy observed under full irrigation conditions. The findings provide a basis for using the CSM-CROPGRO-Peanut model to develop suitable irrigation and nitrogen application regimes for peanuts under mulched drip irrigation in Xinjiang.
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http://dx.doi.org/10.3390/plants14040614 | DOI Listing |
Pediatr Infect Dis J
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From the Department of Pediatrics.
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J Air Waste Manag Assoc
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Department of Materials Science and Tecnology, Federal University of Bahia, Salvador, Brazil.
The accurate estimation of methane generation in landfills is crucial for effective greenhouse gas management and energy recovery, requiring site-specific assessments due to the inherent variability in waste composition and properties before and after disposal. This study investigates the uncertainties associated with methane generation predictions by employing a combination of stoichiometric methods, Biochemical Methane Potential (BMP) assays, and Bayesian inference. Fresh and aged (1-year-old and 5-year-old) samples collected in the tropical Saravan dump site in Gilan, Iran, were used to evaluate the waste's methane generation potential and degradation rate in the field.
View Article and Find Full Text PDFNanoscale
March 2025
Institute of Physical and Theoretical Chemistry, University of Tübingen, Tübingen (Baden-Württemberg), Germany.
Hexagonal (β-) NaYF and LiYF doped with trivalent lanthanide ions (Ln, , Er, Tm, and Yb) are well-known photon upconverting materials. This property is crucially determined by the precise location of the Ln dopant ions and their closest neighbouring ions in the host material. However, due to the inherent disorder of the crystal structures the atomistic structure of a disordered crystal such as β-NaYF is not unambiguously provided by X-ray diffraction techniques.
View Article and Find Full Text PDFWorld J Urol
March 2025
Desai Sethi Urology Institute, University of Miami, Miller School of Medicine, Miami, FL, USA.
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