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
Authors
Haftamu Gebretsadik Gebrehiwot Jens Bernt Aune Ole Martin Eklo Torfinn Torp Lars Olav BrandsæterAbstract
Field experiments were conducted in 2015 and 2016 to study the effect of tillage frequency, seed rate, and glyphosate on teff and weeds. The experiments were arranged in a split plot design with three replications consisting of tillage frequency (conventional, minimum, and zero tillage) as the main plot and the combination of seed rate (5, 15, and 25 kg ha−1) and glyphosate (with and without) as subplots. Results showed that zero tillage reduced teff biomass yield by 15% compared to minimum tillage and by 26% compared to conventional tillage. Zero tillage and minimum tillage also diminished grain yield by 21% and 13%, respectively, compared to conventional tillage. Lowering the seed rate to 5 kg ha−1 reduced biomass yield by 22% and 26% compared to 15 and 25 kg ha−1, respectively. It also reduced the grain yield by around 21% compared to 15 and 25 kg ha−1 seed rates. Conventional tillage significantly diminished weed density, dry weight, and cover by 19%, 29%, and 33%, respectively, compared to zero tillage. The highest seed rate significantly reduced total weed density, dry weight, and cover by 18%, 19%, and 15%, respectively, compared to the lowest seed rate. Glyphosate did not affect weed density but reduced weed dry weight by 14% and cover by 15%. Generally, sowing teff using minimum tillage combined with glyphosate application and seed rate of 15 kg ha−1 enhanced its productivity and minimized weed effects.
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Authors
Michel VerheulAbstract
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Authors
Christina Hoerterer Jessica Petereit Gisela Lannig Johan Johansen Luis E. C. Conceição Bela H. BuckAbstract
One part of aquaculture sustainability is reducing the environmental footprint of aquaculture feeds. For European aquaculture, this means finding feed ingredients that are produced within the economic community, and that are not in conflict with human consumption. This is especially challenging when formulating diets for carnivorous fish such as turbot with low tolerance to fishmeal replacement that are both nutritious and economically and environmentally sustainable. Therefore, we investigated the effects of two novel and innovative feed formulation concepts on growth and feed performance and the nutritional status of market-sized turbot in a recirculating aquaculture system. In a 16-week feeding trial, 440 turbot (300 ± 9 g) were fed twice a day with a control diet (CTRL), based on a commercial formulation, and four experimental diets. The experimental diets were designed to investigate the effects of two formulations concepts based on sustainable terrestrial plant proteins (NoPAP) or processed animal proteins (PAP) and of 30% and 60% fishmeal replacement with emerging feed ingredients (fisheries by-products, insect meal and fermentation biomass). Turbot from the CTRL group had a similar growth and feed performance than fish fed the NoPAP30 formulation, with a significant decline of performance in the fish fed both PAP formulations and the NoPAP60. Comparing the two formulation concepts with each other the voluntary feed intake and protein efficiency ratio on tank basis as well as the individual weight gain and relative growth rate was significantly higher in the fish from the NoPAP groups than PAP groups. Furthermore, the apparent digestibility of nutrients and minerals was significantly reduced in the fish fed with the diets with 30% and 60% fishmeal replacement level compared to the fish from the CTRL group. In conclusion, the performance of the fish fed the NoPAP30 formulation concept highlights the potential of the used combination of sustainable ingredients, such as fisheries by-products, insect meal, microbial biomass and plant protein for turbot. Furthermore, this study shows that turbot has a higher tolerance to the incorporation of plant and insect protein than of processed animal protein.
Abstract
Fishbones contain significant amounts of plant nutrients. Fish residues may be preserved by acidification to pH < 4, which may affect the chemical extractability, and the plant availability of nutrients when applied as fertilisers. Grinded bone material from cod (Gadus morhua) heads was mixed with formic acid to investigate if this would increase the concentrations of ammonium lactate–acetate (AL)-extractable nutrients. Two degrees of fineness of fishbones (coarse 2–4 mm; fine < 0.71 mm) were compared at pH 3.0 and 4.0 plus a water control in a laboratory study over 55 days. Samples for measurement of AL-extractable P, Ca, Mg and K were taken on day 2, 15, 34 and 55. Whereas more formic acid and thereby lower pH clearly increased the concentrations of AL-extractable calcium (Ca-AL) and magnesium (Mg-AL), AL-extractable phosphorus (P-AL) was only significantly increased in finely grinded bones at pH 3. After 34 days at pH 3, 6% of the total content of P was extracted by AL in fine fishbones. In the water control, about 1% of the P was extracted, possibly from phospholipids. This P-AL concentration was well above P-AL extracted from acidified coarse fishbones (pH 3 and 4) and from fine fishbones acidified to pH 4. With acidification, about 30% of total Ca and 100% of total Mg were extracted by AL, and the Ca-AL and Mg-AL concentrations were closely correlated. A possible reason for lower P-AL in coarse fishbones at pH 3 and 4, and in fine fishbones at pH 4 than in water controls may be a precipitation of apatite from phospholipids and dissolved calcium.
Authors
Michel VerheulAbstract
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Authors
Diogo N. Cosenza Petteri Packalén Matti Maltamo Petri Varvia Janne Räty Paula Soares Margarida Tomé Jacob L. Strunk Lauri KorhonenAbstract
Semi- and nonparametric models are popular in the area-based approach (ABA) using airborne laser scanning. It is unclear, however, how many predictors and training plots are needed to provide accurate predictions without overfitting. This work aims to explore these limits for various approaches: ordinary least squares regression (OLS), generalized additive models (GAM), least absolute shrinkage and selection operator (LASSO), random forest (RF), support vector machine (SVM), and Gaussian process regression (GPR). We modeled timber volume (m3·ha–1) for four boreal sites using ABA with 2–39 predictors and 20–500 training plots. OLS, GAM, LASSO, and SVM overfitted as the number of predictors approached the number of training plots. They required ≥15 plots per predictor to provide accurate predictions (RMSE ≤30%). GAM required ≥250 plots regardless of the number of predictors. The number of predictors only mildly affected RF and GPR, but they required ≥200 and ≥250 training plots, respectively. RF did not overfit in any circumstances, whereas GPR overfit even with 500 training plots. Overall, using up to 39 predictors did not generally result in overfit, and for most model types, it resulted in better accuracy for sufficiently large datasets (≥250 plots).