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.
2017
Forfattere
Nesrin Colak Anja K. Primetta Kaisu R. Riihinen Laura Jaakola Jiři Grúz Miroslav Strnad Hülya Torun Faik Ahmet AyazSammendrag
Bilberries and their products are popular worldwide and represent a very interesting source of dietary antioxidants. Berries of eight different-colored and non-pigmented bilberry (Vaccinium myrtillus L.) samples from Finland were evaluated in terms of antioxidant capacity and total phenolic compounds (range, 220.06 – 3715.21 mg/100 g dw) and total monomeric anthocyanin (range, 206.18 – 867.52 mg/100 g dw) contents. Delphinidin (range, 5915.93–18108.39 μg /g dw) was the major anthocyanin moiety, while sinapic acid was the major phenolic acid in the free form (range, 0.01 – 6.06 μg /g dw), and p-coumaric acid in the ester (range, 26.39 – 110.78 μg /g dw), glycoside (range, 15.83 – 57.73 μg /g dw) and ester-bound (range, 2.32 – 14.20 μg /g dw) forms. The white colored berry samples did not contain any anthocyanins, but the colored berries did contain them. Antioxidant capacity was much higher in colored (pink to blue/black) berry samples than in the white sample, and it was more related to the total phenolic concentration rather than to the anthocyanin concentration. This is the first time that these different-colored berry phenotypes of bilberry (V. myrtillus L.) have been analyzed within the same study.
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The absorption of anthropogenic CO 2 by the oceans is causing a reduction in the pH of the surface waters termed ocean acidification (OA). This could have substantial effects on marine coastal environments where fleshy (non-calcareous) macroalgae are dominant primary producers and ecosystem engineers. Few OA studies have focused on the early life stages of large macroalgae such as kelps. This study evaluated the effects of seawater pH on the ontogenic development of meiospores of the native kelp Macrocystis pyrifera and the invasive kelp Undaria pinnatifi da , in south-eastern New Zealand. Meiospores of both kelps were released into four seawater pH treatments (pH T 7.20, extreme OA predicted for 2300; pH T 7.65, OA predicted for 2100; pH T 8.01, ambient pH; and pH T 8.40, pre-industrial pH) and cultured for 15 d. Meiospore germination, germling growth rate, and gametophyte size and sex ratio were monitored and measured. Exposure to reduced pH T (7.20 and 7.65) had pos itive effects on germling growth rate and gametophyte size in both M. pyrifera and U. pinnatifida , whereas, higher pH T (8.01 and 8.40) reduced the gametophyte size in both kelps. Sex ratio of gametophytes of both kelps was biased toward females under all pH T treatm ents, except for U. pinnatifida at pH T 7.65. Germling growth rate under OA was significantly higher in M. pyrifera compared to U. pinnatifida but gametophyte development was equal for both kelps under all seawater pH T treatments, indicating that the microscopic stages of the native M. pyrifera and the invasive U. pinnatifida will respond similarly to OA.
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Today’s modern precision agriculture applications have a huge demand for data with high spatial and temporal resolution. This leads to the need of unmanned aerial vehicles (UAV) as sensor platforms providing both, easy use and a high area coverage. This study shows the successful development of a prototype hybrid UAV for practical applications in precision agriculture. The UAV consists of an off-the-shelf fixed-wing fuselage, which has been enhanced with multi-rotor functionality. It was programmed to perform pre-defined waypoint missions completely autonomously, including vertical take-off, horizontal flight, and vertical landing. The UAV was tested for its return-to-home (RTH) accuracy, power consumption and general flight performance at different wind speeds. The RTH accuracy was 43.7 cm in average, with a root-mean-square error of 39.9 cm. The power consumption raised with an increase in wind speed. An extrapolation of the analysed power consumption to conditions without wind resulted in an estimated 40 km travel range, when we assumed a 25 % safety margin of remaining battery capacity. This translates to a maximal area coverage of 300 ha for a scenario with 18 m/s airspeed, 50 minutes flight time, 120 m AGL altitude, and a desired 70 % of image side-lap and 85 % forward-lap. The ground sample distance with an in-built RGB camera was 3.5 cm, which we consider sufficient for farm-scale mapping missions for most precision agriculture applications.
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Small-area estimation is a subject area of growing importance in forest inventories. Modelling the link between a study variable Y and auxiliary variables X— in pursuit of an improved accuracy in estimators—is typically done at the level of a sampling unit. However, for various reasons, it may only be possible to formulate a linking model at the level of an area of interest (AOI). Area-level models and their potential have rarely been explored in forestry. This study demonstrates, with data (Y = stem volume per ha) from four actual inventories aided by aerial laser scanner data (3 cases) or photogrammetric point clouds (1 case), application of three distinct models representing the currency of area-level modelling. The studied AOIs varied in size from forest management units to forest districts, and municipalities. The variance explained by X declined sharply with the average size of an AOI. In comparison with a direct estimate mean of Y in an AOI, all three models achieved practically important reduction in the relative root-mean-squared error of an AOI mean. In terms of the reduction in mean-squared errors, a model with a spatial location effect was overall most attractive. We recommend the pursuit of a spatial model component in area-level modelling as promising within the context of a forest inventory.
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Forest stands are important units of management. A stand-by-stand estimation of the mean and variance of an attribute of interest (Y) remains a priority in forest enterprise inventories. The advent of powerful and cost effective remotely sensed auxiliary variables (X) correlated with Y means that a census of X in the forest enterprise is increasingly available. In combination with a probability sample of Y, the census affords a modeldependent stand-level inference. It is important, however, that the sampling design affords an estimation of possible stand-effects in the model linking X to Y.We demonstrate, with simulated data, that failing to quantify non-zero stand-effects in the intercept of a linear population-level model can lead to a serious underestimation of the uncertainty in a model-dependent estimate of a stand mean, and by extension a confidence interval with poor coverage.We also provide an approximation to the variance of stand-effects in an intercept for the case when a sampling design does not afford estimation. Furthermore, we propose a method to correct a potential negative bias in an estimate of the variance of stand-effects when a sampling design prescribes few stands with small within-stand sample sizes.
Forfattere
Shuhe Zhao Dianmin Cong Kexun He Hong Yang Zhihao QinSammendrag
Droughts cause huge losses of society and environment, therefore it is important to study the spatial-temporal pattern of drought. The traditional remote sensing drought indices (AVI, VCI and TCI) only consider the single factor representing the soil moisture (surface temperature or NDVI). The comprehensive remote sensing drought indices (VSWI and TVDI) can estimate the soil moisture more accurately, but they are not suitable for large scale region especially with great elevation variation. In this study, a modifed Temperature Vegetation Drought Index (mTVDI) was constructed based on the correction of elevation and dry edge. Compared with the traditional drought indices, mTVDI had a better relationship with soil moisture in all selected months (R=−0.376, −0.406, −0.459, and −0.265, p<0.05). mTVDI was used to analyze the spatial-temporal patterns of drought in China from 1982 to 2010. The results showed that droughts appeared more frequently in Northwest China and the southwest of Tibet while drought centers of North and Southwest China appeared in Huanghuaihai Plain and Yunnan-Guizhou Plateau respectively. The frequency of drought was increasing as a whole while the frequency of severe drought increased signifcantly by 4.86% and slight drought increased slowly during 1982 to 2010. The results are useful for the understanding of drought and policy making of climate change.
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Several mathematical models have been proposed for describing particle‐size distribution (PSD) data, but their characteristics and accuracy have not been investigated for the < 0.002, 0.002–0.05 and 0.05–2.0‐mm fractions separately. Therefore, the primary objective of this study was to examine the characteristics of various PSD models and to evaluate the accuracy of fitting to the entire PSD curve and to each of the three fractions separately. Thirty‐six PSD models were fitted to the experimental data of 160 soil samples from Iran. The beerkan estimation of soil transfer (BEST), Fredlund unimodal and bimodal, two‐ and three‐parameter Weibull, Rosin–Rammler and van Genuchten models provided the best fit to the experimental data of the three size fractions above, but with a different order of performance for the different fractions. For all textural fractions, the following models performed substantially less well than the other models: the offset‐non‐renormalized lognormal, simple lognormal, S‐curve, Schuhmann, Yang, Turcotte and Gompertz models. A comparison of the overall accuracy and simplicity of the models indicated that the BEST, two‐ and three‐parameter Weibull and Rosin–Rammler models provided the best fit to the experimental data for the entire curve, which is similar but does not correspond fully to the findings of a similar, earlier study. We found that the number of model parameters and the type of equation did not explain the models' fitting capabilities. We also found that the iterated function system (IFS) model performed better than the PSD models for all fractions. Comprehensive comparisons of PSD models will be of value to future model users, but it is important to note that such comparisons will remain dataset dependent. This is likely to continue until they are tested on a near‐infinite synthetic dataset that covers all possible data options.
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«This is a perspective for the article 2016 Environ. Res. Lett. 11 095010”