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.
2023
Sammendrag
Pandora neoaphidis is a common entomopathogenic fungus on Sitobion avenae, which is an important aphid pest on cereals in Europe. Pandora neoaphidis is known to cause epizootics (i.e. an unusually high prevalence of infected hosts) and the rapid collapse of aphid populations. We developed a weather-driven mechanistic model of the winter wheat-S. avenae-P. neoaphidis system to simulate the dynamics from spring to harvest. Aphid immigration was fixed at a rate that would lead to a pest outbreak, if not controlled by the fungus. We estimated the biocontrol efficacy by running pair-wise simulations, one with and one without the fungus. Uncertainty in model parameters and variation in weather was included, resulting in a range of simulation outcomes, and a global sensitivity analysis was performed. We identified two key understudied parameters that require more extensive experimental data collection to better assess the fungus biocontrol, namely the fungus transmission efficiency and the decay of cadaver, which defines the time window for possible disease transmission. The parameters with the largest influence on the improvement in yield were the weather, the lethal time of exposed aphids, the fungus transmission efficiency, and the humidity threshold for fungus development, while the fungus inoculum in the chosen range (between 10 and 70% of immigrant aphids carrying the fungus) was less influential. The model suggests that epizootics occurring early, around Zadoks growth stage (GS) 61, would lead to successful biocontrol, while later epizootics (GS 73) were a necessary but insufficient condition for success. These model predictions were based on the prevalence of cadavers only, not of exposed (i.e. infected but yet non-symptomatic) aphids, which in practice would be costly to monitor. The model suggests that practical Integrated Pest Management could thus benefit from including the cadavers prevalence in a monitoring program. We argue for further research to experimentally estimate these cadaver thresholds.
Sammendrag
Temperature and humidity were measured in 28 vegetable stores and corelated to quality of stored vegetable through two storage seasons. The vegetables swede, carrot and celeriac were grown at one site within each of the four regions in Norway ROG, MID, INN and OSL, respectively. After harvesting, the vegetables were weighed and visually assessed for any injuries or diseases and stored in different stores within the same region as grown. Four bags dug down in four storage bins in each store. Temperature and humidity were logged in each bag as well as on the top of each bin and on wall of the storage. In general, we found significant differences in the storage quality between the different storages as well as between regions. Correlating data on quality with temperature data shows for carrot a tendency to an increase in the proportion of fresh roots and reduction in incidence of tip-rot by an increased average temperature during the first two weeks of storage. This corresponds to results from tested various wound healing treatments. An increase in accumulated temperature during the storage period showed a tendency to increase the emergence of tip-rot and reduce the proportion of fresh roots. For celeriac, the effect of temperature varied between years, possibly due to a large difference in quality in the two test years, and it was difficult to draw any conclusion. In swede, the results suggest that a decrease in temperature in the first two weeks of storage increased the risk of the symptom shown as black veins in the phloem. Nutrient status was found to be a possibly predisposing factor for reduced storage quality in celeriac. Balance of boron (B) to calcium (Ca) and zinc (Zn) were studied in two sites. Highest incidence of brown spots and lowest proportion of fresh roots following storage was found in celeriac with the lowest Ca/B ratio in leaves, lowest content of Zn in the leaves and roots and lowest soil pH.
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Weeds affect crop yield and quality due to competition for resources. In order to reduce the risk of yield losses due to weeds, herbicides or non-chemical measures are applied. Weeds, especially creeping perennial species, are generally distributed in patches within arable fields. Hence, instead of applying control measures uniformly, precision weeding or site-specific weed management (SSWM) is highly recommended. Unmanned aerial vehicle (UAV) imaging is known for wide area coverage and flexible operation frequency, making it a potential solution to generate weed maps at a reasonable cost. Efficient weed mapping algorithms need to be developed together with UAV imagery to facilitate SSWM. Different machine learning (ML) approaches have been developed for image-based weed mapping, either classical ML models or the more up-to-date deep learning (DL) models taking full advantage of parallel computation on a GPU (graphics processing unit). Attention-based transformer DL models, which have seen a recent boom, are expected to overtake classical convolutional neural network (CNN) DL models. This inspired us to develop a transformer DL model for segmenting weeds, cereal crops, and ‘other’ in low-resolution RGB UAV imagery (about 33 mm ground sampling distance, g.s.d.) captured after the cereal crop had turned yellow. Images were acquired during three years in 15 fields with three cereal species (Triticum aestivum, Hordeum vulgare, and Avena sativa) and various weed flora dominated by creeping perennials (mainly Cirsium arvense and Elymus repens). The performance of our transformer model, 1Dtransformer, was evaluated through comparison with a classical DL model, 1DCNN, and two classical ML methods, i.e., random forest (RF) and k-nearest neighbor (KNN). The transformer model showed the best performance with an overall accuracy of 98.694% on pixels set aside for validation. It also agreed best and relatively well with ground reference data on total weed coverage, R2 = 0.598. In this study, we showed the outstanding performance and robustness of a 1Dtransformer model for weed mapping based on UAV imagery for the first time. The model can be used to obtain weed maps in cereals fields known to be infested by perennial weeds. These maps can be used as basis for the generation of prescription maps for SSWM, either pre-harvest, post-harvest, or in the next crop, by applying herbicides or non-chemical measures.
Sammendrag
Appropriate weed control measures during the renewal phase of temporary grasslands are critical to ensure high yields during the whole grassland lifecycle. The aim of this study was to determine which integrated grassland renewal strategy can most effectively control annual weeds in the sowing year and delay perennial weed re-establishment. Four split-plot trials were established at three sites dominated by Rumex spp. along a south-north gradient in Norway. The annual and perennial weed abundance was recorded during the sowing year and two or three production years. Main plots tested seven renewal strategies: 1. Spring plowing, 2. Spring plowing+companion crop (CC), 3. Summer cut+plowing, 4. Summer glyphosate+plowing, 5. Summer glyphosate+harrowing, 6. Late spring glyphosate+plowing, 7. Fall glyphosate+spring plowing+CC. Strategies 1–4 were tested in all four trials, strategy 5 in three trials, strategy 6 in two trials and strategy 7 in one trial. Plowing was performed at 20–25 cm depth, rotary harrowing at 15 cm depth, and glyphosate was applied at 2160 g a.i. ha-1. CC was spring barley (Hordeum vulgare). Subplots tested selective herbicide spraying (yes/no) in the sowing year. Results showed that effects of renewal strategies were often site-specific and differed between the sowing year and production years. Spring renewal resulted in higher perennial weed abundance than summer renewal in two out of four trials (by 3 and 12 percentage points, over all production years), and glyphosate followed by harrowing drastically increased Rumex spp. in one out of three trials (by 18 percentage points over all production years). CCs only significantly reduced perennial weed abundance in one trial (by 8 percentage points over all production years). In comparison, the selective herbicides had a strong effect on annual and perennial weeds in the sowing year in all trials. Selective herbicides reduced the weed cover from 32% to 7% cover, and averaged over the production years and sites, the perennial weed biomass fraction was 6 percentage points lower where herbicides had been applied. We conclude that while the tested renewal strategies provided variable and site-specific perennial weed control, selective herbicides were effective at controlling Rumex spp. and other perennial dicot weeds in the first two production years.
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Denne rapporten gjør rede for metoder brukt for å fremstille temakart for framskrivninger av klima i Tønsberg og Drammen for perioden 2040-2070. Kartene skal gjøres tilgjengelige i kommunenes kartportaler. Temakartene går inn i en større leveranse av temakart over arealdekkets rolle i arbeidet med klimatilpasning, samt klimagassutslipp fra arealbruk og arealbruksendringer for Tønsberg og Drammen kommune. Oppdragene er finansiert med Klimasats-ordningen til Miljødirektoratet.
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