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.
2023
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Abstract
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.
Abstract
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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No abstract has been registered
2022
Authors
Raghuram Badmi Torstein Tengs May Bente Brurberg Abdelhameed Elameen Yupeng Zhang Lisa Karine Haugland Carl Gunnar Fossdal Timo Hytönen Paal Krokene Tage ThorstensenAbstract
Grey mold caused by the necrotrophic fungal pathogen Botrytis cinerea can affect leaves, flowers, and berries of strawberry, causing severe pre- and postharvest damage. The defense elicitor β-aminobutyric acid (BABA) is reported to induce resistance against B. cinerea and many other pathogens in several crop plants. Surprisingly, BABA soil drench of woodland strawberry (Fragaria vesca) plants two days before B. cinerea inoculation caused increased infection in leaf tissues, suggesting that BABA induce systemic susceptibility in F. vesca. To understand the molecular mechanisms involved in B. cinerea susceptibility in leaves of F. vesca plants soil drenched with BABA, we used RNA sequencing to characterize the transcriptional reprogramming 24 h post-inoculation. The number of differentially expressed genes (DEGs) in infected vs. uninfected leaf tissue in BABA-treated plants was 5205 (2237 upregulated and 2968 downregulated). Upregulated genes were involved in pathogen recognition, defense response signaling, and biosynthesis of secondary metabolites (terpenoid and phenylpropanoid pathways), while downregulated genes were involved in photosynthesis and response to auxin. In control plants not treated with BABA, we found a total of 5300 DEGs (2461 upregulated and 2839 downregulated) after infection. Most of these corresponded to those in infected leaves of BABA-treated plants but a small subset of DEGs, including genes involved in ‘response to biologic stimulus‘, ‘photosynthesis‘ and ‘chlorophyll biosynthesis and metabolism’, differed significantly between treatments and could play a role in the induced susceptibility of BABA-treated plants.
Authors
Heidi Udnes Aamot Simeon Rossmann Erik Lysøe Guro Brodal Birgitte Henriksen Ruth Dill-Macky Carl Gunnar Fossdal Ingerd Skow HofgaardAbstract
We used metabarcoding of ITS 1 and 2 to compare the mycobiome of Norwegian spring wheat seed lots of two commonly grown spring wheat varieties (Mirakel and Zebra) harvested in 2016 and 2017. The seed lots varied in germination and were grouped according to high and low germination (≥90% and <90% germinated seeds, respectively) determined by the ISTA germination method. In addition, the percentage of each seed lot infested by the most important wheat pathogens (Microdochium spp., Fusarium spp., and Parastagonospora nodorum) was determined using a plate-out test on PDA, and species-specific qPCR was used to quantify the amount of DNA of F. avenaceum, F. culmorum, F. graminearum, F. poae, M. majus, M. nivale, and P. nodorum. Our study indicated that the presence of Microdochium was most associated with poor germination (which is as expected), while P. nodorum; although present at relatively high levels, apparently had limited impact on germination. Among the species quantified by qPCR, M. majus was the most abundant, F. avenaceum was detected at low levels, whereas the other fusaria were barely detected. Metabarcoding data indicated a negative association between the presence of the fungal genus Neoascochyta and germination, while Pyrenophora and Alternaria species appeared positively associated with germination. Our results indicated some co-existence patterns between fungal species, including both pathogenic and non-pathogenic species, with some species combinations associated with the germination potential of wheat seed.
Authors
Sunniva Løwø Simeon Rossmann Marte Persdatter Tangvik Monica Skogen Solveig Haukeland May Bente BrurbergAbstract
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Authors
Yupeng Zhang Guangxun Fan Tuomas Toivenen Torstein Tengs Igor A. Yakovlev Javier Andrés Paal Krokene Timo Hytönen Paul Grini Carl Gunnar FossdalAbstract
No abstract has been registered