Newest publications
Discovering novel bioherbicides: the impact of hemp-derived phytocannabinoid applications on Zea mays L. and relevant weeds
(2024) Merkle, Michael; Gerhards, Roland
In addition to competition, phytotoxic plant metabolites contribute to the weed-suppressing properties of cover crops, which could be the basis for the development of novel bioherbicides. We investigated the impact of five Cannabis sativa L. -derived neutral phytocannabinoids and an aqueous C. sativa tissue extract (HE) at six concentrations on the germination rate (GR) and seedling root length (RL) of Zea mays L., two monocotyledonous and two dicotyledonous weed species in laboratory Petri dish bioassays. Additionally, the effect of pre-emergence applications of HE, cannabidiol (CBD), and cannabidivarin (CBDV) formulations on GR and shoot dry matter (SDM) were examined in greenhouse pot studies. The effects of phytocannabinoids and HE were analyzed in dose-response curves. For the highest rates, the effects on GR, RL and SDM were calculated by ANOVA and HSD test (p < 0.05). HE exhibited the greatest suppression on GR and RL for all plant species in the Petri dish bioassay, with RGR, RL exceeding −90%. Phytocannabinoids reduced mainly RL of all plants and decreased the GR of most weed species. Effects varied among plants and phytocannabinoids, with CBDV and CBD showing similar high inhibitory effects on RL as HE in the Petri dish bioassay. All pre-emergence applications resulted in a positive RGR across all studied plants and in a positive RSDM in Z. mays and Echinochloa crus-galli (L.) P. Beauv, whereas in the other weed species the RSDM was negative. In conclusion, phytocannabinoids play a major role in weed suppression of HEs. CBDV and CBD are the most promising candidates for bioherbicide development especially against annual dicotyledonous weed species.
Effects of elevated atmospheric CO2 and its interaction with temperature and nitrogen on yield of barley (Hordeum vulgare L.): a meta-analysis
(2022) Gardi, Mekides Woldegiorgis; Haussmann, Bettina I. G.; Malik, Waqas Ahmed; Högy, Petra
Aims: The general aim of this meta-analysis is to synthesize and summarize the mean response of barley yield variables to elevated CO2 (eCO2) and how temperature and nitrogen (N) affect the CO2-induced yield responses of barley. Methods: A meta-analysis procedure was used to analyze five yield variables of barley extracted from 22 studies to determine the effect size and the magnitude concerning eCO2 and its interaction with temperature and N. Results: CO2 enrichment increased aboveground biomass (23.8%), grain number (24.8%), and grain yield (27.4%). The magnitude of the responses to eCO2 was affected by genotype, temperature, nitrogen, and CO2 exposure methods. Genotype “Anakin” shows the highest CO2 response of aboveground biomass (47.1%), while “Bambina” had the highest grain number (58.4%). Grain yield response was observed to be higher for genotypes “Alexis” (38.1%) and “Atem” (33.7%) under eCO2. The increase of aboveground biomass and grain yield was higher when plants were grown under eCO2 in combination with higher N (151–200 kg ha−1). The interaction between eCO2 and three different temperature levels was analyzed to identify the impacts on barley yield components. The results revealed that the CO2-induced increase in grain number and grain yield was higher in combination with a temperature level of 21–25 °C as compared to lower levels (< 15 and 16–20 ℃). The response of barley yield to eCO2 was higher in growth chambers than in other CO2 exposure methods. Moreover, a higher response of aboveground biomass and grain yield to eCO2 was observed for pot-grown plants compared to field-grown.ConclusionsOverall, results suggest that the maximal barley production under eCO2 will be obtained in combination with high N fertilizer and temperature levels (21–25 °C).
Trade and welfare effects of a potential free trade agreement between Japan and the United States
(2022) Walter, Timo
This paper addresses the trade and welfare implications of a bilateral trade agreement between the U.S. and Japan. In 2019, the two countries signed a “stage one” trade agreement, with the U.S.-Japan Trade Agreement (USJTA) and the U.S.-Japan Digital Trade Agreement as two small trade agreements. A comprehensive bilateral free trade agreement (FTA) is currently under discussion between Washington and Tokyo, with the U.S. government alternatively joining the Comprehensive and Progressive Agreement for the Trans-Pacific Partnership (CPTPP). Based on the theoretical model of Caliendo and Parro (Rev Econ Stud, 82(1):1–44, 2015) , I analyze the welfare gains of such a bilateral FTA in the style of Aichele et al. (Where is the value added? China’s WTO entry, trade and value chains, ZBW-Deutsche Zentralbibliothek für Wirtschaftswissenschaften, Leibniz, 2014). I simulate trade and welfare impacts for the USJTA and the U.S.-Japan Digital Trade Agreement, as well as for a deep bilateral FTA. In addition, I examine and compare the welfare implications of the established CPTPP with the scenario of the U.S. or China joining CPTPP. My findings show that Japan’s welfare increases by 0.3% and U.S. welfare increases by 0.14% as a result of the FTA. Welfare of both countries would increase if the U.S. entered CPTPP, with Japanese welfare being even higher if China acceded to CPTPP.
Oral supplementation of choline attenuates the development of alcohol-related liver disease (ALD)
(2024) Sánchez, Victor; Baumann, Anja; Kromm, Franziska; Yergaliyev, Timur; Brandt, Annette; Scholda, Julia; Kopp, Florian; Camarinha-Silva, Amélia; Bergheim, Ina
Background: Chronic alcohol intake is associated with alterations of choline metabolism in various tissues. Here, we assessed if an oral choline supplementation attenuated the development of alcohol-related liver disease (ALD) in mice.
Methods: Female C57BL/6 J mice (n = 8/group) were either pair-fed a liquid control diet, or a Lieber DeCarli liquid diet (5% ethanol) ± 2.7 g choline/kg diet for 29 days. Liver damage, markers of intestinal permeability and intestinal microbiota composition were determined. Moreover, the effects of choline on ethanol-induced intestinal permeability were assessed in an ex vivo model.
Results: ALD development as determined by liver histology and assessing markers of inflammation (e.g., nitric oxide, interleukin 6 and 4-hydroxynonenal protein adducts) was attenuated by the supplementation of choline. Intestinal permeability in small intestine being significantly higher in ethanol-fed mice was at the level of controls in ethanol-fed mice receiving choline. In contrast, no effects of the choline supplementation were found on intestinal microbiota composition. Choline also significantly attenuated the ethanol-induced intestinal barrier dysfunction in small intestinal tissue ex vivo, an effect almost entirely abolished by the choline oxidase inhibitor dimbunol.
Conclusion: Our results suggest that an oral choline supplementation attenuates the development of ALD in mice and is related to a protection from intestinal barrier dysfunction.
Mechanisms to alleviate over-generalization in XCS for continuous-valued input spaces
(2022) Wagner, Alexander R. M.; Stein, Anthony
In the field of rule-based approaches to Machine Learning , the XCS classifier system (XCS) is a well-known representative of the learning classifier systems family. By using a genetic algorithm (GA), the XCS aims at forming rules or so-called classifiers which are as general as possible to achieve an optimal performance level. A too high generalization pressure may lead to over-general classifiers degrading the performance of XCS. To date, no method exists for XCS for real-valued input spaces (XCSR) and XCS for function approximation (XCSF) to handle over-general classifiers ensuring an accurate population. The Absumption mechanism and the Specify operator, both developed for XCS with binary inputs, provide a promising basis for over-generality handling in XCSR and XCSF. This paper introduces adapted versions of Absumption and Specify by proposing different identification and specialization strategies for the application in XCSR and XCSF. To determine their potential, the adapted techniques are evaluated in different classification problems, i.e., common benchmarks and real-world data from the agricultural domain, in a multi-step problem as well as different regression tasks. Our experimental results show that the application of these techniques leads to significant improvements of the accuracy of the generated classifier population in the applied benchmarks, data sets, multi-step problems and regression tasks, especially when they tend to form over-general classifiers. Furthermore, considering the working principle of the proposed techniques, the intended decrease in overall classifier generality can be confirmed.