Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2024
Abstract
The total phenolic content and antiradical activity in vitro varied significantly among the fruit mesocarps samples extracts of seven plum cultivars. It shows the influence of the cultivar factor on the quantitative composition of phenolic compounds and antiradical activity in vitro of P. domestica fruit mesocarps samples extracts. The highest total phenolic content and the strongest antiradical activ ity in vitro was determined in the fruit mesocarps samples extracts of the cultivar 'Čačanska Najbolja' (bred in Serbia). The fruit mesocarps from this cultivar could be valuable for the future researches – determination of the qualitative and quantitative composition of the individual phenolic compounds.
Abstract
Context Traditional critical nitrogen (N) dilution curve (CNDC) construction for N nutrition index (NNI) determination has limitations for in-season crop N diagnosis and recommendation under diverse on-farm conditions. Objectives This study was conducted to (i) develop a new rice (Oryza sativa L.) critical N concentration (Nc) determination approach using vegetation index-based CNDCs; and (ii) develop an N recommendation strategy with this new Nc determination approach and evaluate its reliability and practicality. Methods Five years of plot and on-farm experiments involving three japonica rice varieties were conducted at fourteen sites in Qixing Farm, Northeast China. Two machine learning (ML) methods, random forest (RF) and extended gradient boosting (XGBoost) regression, were used to fuse multi-source data including genotype, environment, management, growth stage, normalized difference vegetation index (NDVI) and normalized difference red edge (NDRE) from portable active canopy sensor RapidSCAN. The CNDC was established using NDVI and NDRE instead of aboveground biomass (AGB) measured by destructive sampling. A new in-season N diagnosis and recommendation strategy was further developed using direct and indirect NNI prediction using multi-source data fusion and ML models. Results The new CNDC based on NDVI or NDRE explained 94−96 % of Nc variability in the evaluation dataset when it was coupled with environmental and agronomic factors using ML models. The ML-based PNC and NNI prediction models explained 85 % and 21–36 % more variability over simple regression models using NDVI or NDRE in the evaluation dataset, respectively. The new in-season N diagnosis strategy using the NDVI and NDRE-based CNDCs and plant N concentration (PNC) predicted with RF model and multi-source data fusion performed slightly better than direct NNI prediction, explaining 7 % more of NNI variability and achieving 89 % of the areal agreement for N diagnosis across all evaluation experiments. Integrating this new N management strategy into the precision rice management system (as ML_PRM) increased yield, N use efficiency (NUE) and economic benefits over farmer’s practice (FP) by 7–15 %, 11–71 % and 4–16 % (161–596 $ ha−1), respectively, and increased NUE by 11–26 % and economic benefits by 8–97 $ ha−1 than regional optimum rice management (RORM) under rice N surplus status under on-farm conditions. Conclusions In-season rice N status diagnosis can be improved using NDVI- and NDRE-based CNDC and PNC predicted by ML modeling with multi-source data fusion. Implications The active canopy sensor- and ML-based in-season N diagnosis and management strategy is more practical for applications under diverse on-farm conditions and has the potential to improve rice yield and ecological and economic benefits.
Abstract
No abstract has been registered
Authors
Charles D. Minsavage-Davis G. Matt Davies Siri Vatsø Haugum Pål Thorvaldsen Liv Guri Velle Vigdis VandvikAbstract
No abstract has been registered
Authors
Sanjana De Zoysa Jeewanthi Sirisena Helani Perera Shalinda Fernando Miyuru Gunathilake Upaka RathnayakeAbstract
Rainfall Intensity Duration Frequency (IDF) curves can be identified as a major role in the planning of urban drainage infrastructure. Sri Lanka, which is an island surrounded by the Indian Ocean, is frequently exposed to various climatic alterations. Sri Lanka has specific region-wise IDF relationships for the entire country, however, these IDF curves were developed more than 30 years ago. Many in-situ rainfall observations in Sri Lanka have insufficient record lengths and the absence of finer time scale records (e.g. 15 min, hourly) leading to unreliable IDF curve developments. Given this importance, the present paper demonstrates the application of Satellite-based Precipitation Product (SbPP) daily rainfall in developing IDF curves for Sri Lanka. Rainfall satellite estimates derived from Integrated Multi-satellite Retrievals for GPM (IMERG), Tropical Rainfall Measuring Mission (TRMM-3B42), and Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR) have been used to evaluate the ability of application of remote sensing data to develop IDF curves for Sri Lanka against rain gauge (RG) data. Our study breaks new ground by generating 50 IDF curves tailored to specific locations covering the whole county Sri Lanka, using daily rainfall data from RGs and three SbPPs during the period between 1990 and 2019. This marks a significant departure from the conventional approach, offering a more granular understanding of rainfall patterns in the country. By providing IDF curves for individual locations, our research presents a novel contribution to Sri Lanka's IDF history. At first, to evaluate the accuracy of SbPPs, statistical analysis was conducted using continuous and categorical evaluation indices. Second, IDF curves were developed and compared with the presently available IDF curves. Results showcased that IMERG outperformed all SbPPs, while PERSIANN-CDR showed dire performances. The IMERG and TRMM-3B42 products tend to overestimate light precipitation regions in high elevations and overestimate heavy rainfall in low elevations compared to rain gauge data. Rainfall intensities derived by rain gauge data depicted relative changes within ±30% for shorter durations and ±20% for longer durations while SbPPs showed beyond ±30% difference concerning the previously developed IDFs. It was apparent that these products have significant inaccuracies which cannot be neglected when utilizing them in developing IDF curves. This study will be beneficial in solving design problems associated with urban runoff control and disposal where knowing the rainfall intensities of different return periods with different durations is vital.
Authors
May Bente BrurbergAbstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
Female flowering and cone production took place in three Norway spruce progeny tests at ages 17 and 20 years, each planted with full-sib families from a half diallel. The number of cones on individual trees were scored in five classes. More than 50 % of the trees produced cones, and a considerable variation was found among families for the ability to produce cones (precocity) and for the number of clones scored in classes (fruitfulness). Both traits were strongly related to tree heights and diameters at the individual and at the family level. In general, tall trees produced the highest number of cones. However, some families produced many cones even if their average heights were low. In two of the half diallels, estimates of GCA variance components for the number of cones produced had twice the value of the SCA component, indicating additive genetic inheritance of cone production. Heritability estimates of cone scores were 0.10, 0.17 and 0.23, and the genetic correlations between cone production and tree heights were 0.40, 0.50 and 0.35 in the three half-diallels, respectively.
Authors
Jaime Puértolas Pedro Villar-Salvador Enrique Andivia Ishita Ahuja Claudia Cocozza Branislav Cvjetković Jovana Devetaković Julio J. Diez Inger Sundheim Fløistad Petros Ganatsas Barbara Mariotti Marianthi Tsakaldimi Alberto Vilagrosa Johanna Witzell Vladan IvetićAbstract
Drought hardening is a nursery technique aimed to enhance early forest plantation establishment under dry conditions, which is a main limiting factors for plantation success. However, the quantitative effectiveness of drought hardening remains unclear. We conducted a meta-analysis to evaluate the influence of different factors in the effectiveness of drought hardening on seedling post-planting survival and growth. Overall, drought hardening did not significantly affect survival or growth, as several factors induced great heterogeneity, but analyses of those factors explained its effectiveness, especially on survival. A longer time between hardening and transplanting strongly reduced survival. Indoor-grown seedlings did not benefit more from hardening than outdoor-grown seedlings. Evaluations of drought hardening effectiveness in pots showed positive effects on survival but negative effects on growth, while no effects were found in large bed experiments. In field experiments, hardening significantly increased survival and growth with site aridity. Survival benefits were independent of species drought tolerance, measured by osmotic potential at the turgor loss point (πtlp), in moderate to high aridity sites. However, in low aridity sites, hardening increased survival in drought-tolerant species but decreased it in drought-intolerant species. Field results showed that hardening benefited shrubs more than trees in angiosperms. In conclusion, drought hardening at the end of nursery cultivation tend to increase post-planting seedling performance particularly in scenarios limiting post-planting root growth such as in arid climates and pot experiments. Our findings highlight the importance of future research on modelling the interaction between these technical features and species water use strategies..
Abstract
No abstract has been registered