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.
2022
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Authors
Jeannette K. Winsou Ghislain T. Tepa-Yotto Karl Thunes Richard Meadow Manuele Tamò May-Guri SæthreAbstract
Fall armyworm (FAW) Spodoptera frugiperda (J.E. Smith, 1797) (Lepidoptera: Noctuidae) was recorded for the first time in 2016 attacking maize fields in central and west Africa. Soon after, several other regions and countries have reported the pest in almost the entire sub-Saharan Africa. In the present study, we assumed that (i) a variety of alternative plant species host FAW, especially during maize off-season, (ii) a wide range of local parasitoids have adapted to FAW and (iii) parasitoid species composition and abundance vary across seasons. During a two-year survey (from June 2018 to January 2020), parasitoids and alternative host plants were identified from maize and vegetable production sites, along streams and lowlands, on garbage dumps and old maize fields in southern and partly in the central part of Benin during both maize growing- and off-season. A total of eleven new host plant species were reported for the first time, including Cymbopogon citratus (de Candolle) Stapf (cultivated lemon grass), Bulbostylis coleotricha (A. Richard) Clarke and Pennisetum macrourum von Trinius (wild). The survey revealed seven parasitoid species belonging to four families, namely Platygastridae, Braconidae, Ichneumonidae, and Tachinidae associated with FAW on maize and alternative host plants. The most abundant parasitoid species across seasons was the egg parasitoid Telenomus remus (Nixon) (Hymenoptera: Platygastridae). These findings demonstrate FAW capability to be active during the maize off-season in the selected agro-ecologies and provide baseline information for classical and augmentative biocontrol efforts.
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Precision weeding or site-specific weed management (SSWM) take into account the spatial distribution of weeds within fields to avoid unnecessary herbicide use or intensive soil disturbance (and hence energy consumption). The objective of this study was to evaluate a novel machine vision algorithm, called the ‘AI algorithm’ (referring to Artificial Intelligence), intended for post-emergence SSWM in cereals. Our conclusion is that the AI algorithm should be suitable for patch spraying with selective herbicides in small-grain cereals at early growth stages (about two leaves to early tillering). If the intended use is precision weed harrowing, in which also post-harrow images can be used to control the weed harrow intensity, the AI algorithm should be improved by including such images in the training data. Another future goal is to make the algorithm able to distinguish weed species of special interest, for example cleavers (Galium aparine L.).
Authors
Venche Talgø Thomas Jung Ivan Milenković Tamara Corcobado Martin Pettersson May Bente BrurbergAbstract
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Authors
Inge Dox Tore Skrøppa Mieke Decoster Peter Prislan Aina Gascó Jožica Gričar Holger Lange Matteo CampioliAbstract
Historically, the autumn dynamics of deciduous forest trees have not been investigated in detail. However, autumn phenological events, like onset of loss of canopy greenness (OLCG), onset of foliar senescence (OFS) and cessation of wood growth (CWG), have an important impact on tree radial growth and the entire ecosystem's seasonal dynamics. Here, we monitored the leaf and wood phenological events of silver birch (Betula pendula) at four different sites in Ås, southeastern Norway: (a) a natural mature stand, (b) a plantation on former agricultural ground, (c) young natural trees, and (d) young trees in pots under different fertilization levels. The study took place over four consecutive years (from 2017 to 2020), with a particular focus on 2018, a year in which there was a severe summer drought, and the next year, 2019, which featured more normal conditions. First, we provided a description of birch phenology within its mid-north distributional. Second, we showed that drought advanced CWG by about 5 to 6 weeks and it delayed OLCG and OFS up to 30 days. Third, we observed an unexpected advance in OLCG in 2019 compared to 2018 (30 days) and 2020 (14 days). OFS presented similar dynamics as OLCG, whereas CWG was advanced only in 2018. These findings might indicate lag-effects of severe drought on the next year autumn leaf phenology but not on wood growth. On the other hand, the comparison between the natural stand and the plantation showed that, under drought conditions, wood growth is more sensitive to site fertility than autumn leaf phenology. In summary, our study elucidated the autumn dynamics of an important deciduous forest species in the northern temperate zone and showed unexpected impacts of a severely dry and warm summer on the current and next year leaf phenology.
Abstract
No abstract has been registered