Publikasjoner
NIBIOs ansatte publiserer flere hundre vitenskapelige artikler og forskningsrapporter hvert år. Her finner du referanser og lenker til publikasjoner og andre forsknings- og formidlingsaktiviteter. Samlingen oppdateres løpende med både nytt og historisk materiale. For mer informasjon om NIBIOs publikasjoner, besøk NIBIOs bibliotek.
2024
Sammendrag
Background: Soil water and organic carbon (C) are key factors affecting the growth and development of apple seedlings. The objective of the study was to investigate the effects of different soil moisture and glucose supplies on apple seedling growth and soil enzyme activities. We hypothesized that the growth of apple seedlings was affected by soil water and C content through their effects on root structure, plant physiological properties and soil enzymatic activities. A pot experiment consisting of nine treatments was set up, including three water treatments with soil moisture contents at 75–85% (normal irrigation, CK), 65–75% (light water stress, LS), and 55–65% (mild water stress, MS) of the soil field capacity, in combination with three glucose treatments with carbon/nitrogen (C/N) ratio of 7.5 (C1, no adding glucose), 10 (C2) and 15 (C3), respectively. Results: Results showed that the LSC2 treatment significantly increased plant height by 7%, stem diameter by 5% and leaf area by 17%, as compared with LSC1. Also, LSC2 significantly increased root dry weight, root vitality and soil enzyme activities. Moreover, results of leaf photosynthetic, malondialdehyde (MDA), peroxidase (POD), superoxide dismutase (SOD) and proline contents also proved that adding glucose improved the drought resistance of plants. Conclusion: LSC2 treatment is more conducive to the growth of apple seedlings, and application of carbon has a good alleviation effect on plant water stress. The study demonstrated that addition of exogenous glucose alleviated light water deficiency, significantly affected root vitality, and promoted apple seedling growth. © 2024 Society of Chemical Industry.
Sammendrag
Reasonable chemical nitrogen (N) reduction and water-soluble amino acid fertilizers (WAAF) application can mitigate the negative effects of excessive N supply. Here, we reported that a 30% N reduction (T1) led to attenuated plant growth and decreased fruit quality of strawberries, which could be overwhelmingly restored by additional WAAF application (T2). To explore the underlying mechanism, comparative transcriptomic analysis was performed. Results revealed significant expression changes of genes involved in metabolisms of starch and sucrose, ascorbate and aldarate, carbon (C) and N, glyoxylate and dicarboxylate and so on. In consistence with the increased ascorbic acid (AsA) content and sugar/acid ratio, WAAF application upregulated GLDH, SPS and β-GE genes and downregulated APX, ICL and MS genes. Additionally, the differential expression of PK, IDH, GDH and SPX was consistent with the shift from C flux to N metabolism and the improved phosphorus (P) accumulation resulted from WAAF application. Our study will be helpful for understanding the effect of N reduction and WAAF application on strawberry fruit quality.
Forfattere
Jian LiuSammendrag
Det er ikke registrert sammendrag
Forfattere
Helen Baulch J. Venkiteswaran K Painter Jian Liu D Spence K Nugent C Whitfield A Baron P Lloyd-Smith J Elliott H WilsonSammendrag
Det er ikke registrert sammendrag
Forfattere
Jian LiuSammendrag
Det er ikke registrert sammendrag
Forfattere
Jian LiuSammendrag
Det er ikke registrert sammendrag
Sammendrag
Agricultural sustainability is threatened by both water deficit and water excess, especially at the presence of extreme meteorological events resulting from climate change. However, there has been lack of demonstrations on management options with long-term values for agricultural adaptation to runoff. Using 20 years of monitoring data (1993–2012) for two experimental fields in the Canadian Prairies as a case study, we quantified the effects of rainfall characteristics, crop type and biomass, and tillage on growing-season runoff generation using regression analyses and thereafter scenario comparisons. With growing-season gross rainfall ranging between 183 and 456 mm, runoff responses varied between 0 and 59 mm. Over the 20-year study period, 70%–74 % of the growing season runoff was generated by rainfall events >100 mm. Compared to high-intensity tillage, long-term conservation tillage reduced both overall runoff and runoff in large events likely by improving water infiltration. Under both tillage methods, growing-season runoff significantly increased with increasing rainfall but decreased with increasing biomass (R2 range: 0.40–0.58; p range: 0.0007–0.02). At the event level, the rainfall-runoff relationship followed a piecewise regression model (Cd ¼ 0.82; p
Forfattere
Jian LiuSammendrag
Det er ikke registrert sammendrag
Forfattere
Robert BarneveldSammendrag
Det er ikke registrert sammendrag
Forfattere
Yi Zhang Xingru Yang Yijing Feng Zhiyue Dai Zhangmu Jing Yeqing Li Lu Feng Yanji Hao Shasha Yu Weijin Zhang Yanjuan Lu Chunming Xu Junting PanSammendrag
Exploring the complex mechanism of anaerobic digestion with hydrothermal pretreatment (HTAD) for biomass efficiently and optimising the reaction conditions are critical to improving the performance of methane production. This study used H2O automated machine learning (AutoML) for comprehensive prediction, analysis, and targeted optimization of the HTAD system. An IterativeImputer system for data filling was constructed. The comparison of three basic regressors showed that random forest performed optimally for filling (R2 > 0.95). The gradient boosting machine (GBM) model was searched by H2O AutoML to show optimal performance in prediction (R2 > 0.96). The software was developed based on the GBM model, and two prediction schemes were devised. The generalization error of the software was less than 10%. The Shapley Additive exPlanations value showed that solid to liquid ratio, hydrothermal pretreatment (HT) temperature, and particle size have greater potential for improving cumulative methane production (CMP). A Bayesian-HTAD optimization strategy was devised, using the Bayesian optimization to directionally optimize the reaction conditions, and performing experiments to validate the results. The experimental results showed that the CMP was significantly improved by 51.63%. Compared to the response surface methodology, the Bayesian optimization relatively achieved a 2.21–2.50 times greater effect. Mechanism analyses targeting the experiments showed that HT was conducive to improving the relative abundance of Sphaerochaeta, Methanosaeta, and Methanosarcina. This research achieved accurate prediction and targeted optimization for the HTAD system and proposed multiple filling, prediction, and optimization strategies, which are expected to provide an AutoML optimization paradigm for anaerobic digestion in the future.