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
Authors
Yi Zhang Zhangmu Jing Yijing Feng Shuo Chen Yeqing Li Yongming Han Lu Feng Junting Pan Mahmoud Mazarji Hongjun Zhou Xiaonan Wang Chunming XuAbstract
Exploring key factors has important guidance for understanding complex anaerobic digestion (AD) systems. This study proposed a multi-layer automated machine learning framework to understand the complex interactions in AD systems and explore key factors at the environmental factor, microorganisms and system levels. The first layer of the framework identified hydraulic residence time (HRT) as the most important environmental factor, with an optimal range of 33–45 d. In the second layer of the framework, Methanocelleus (optimal relative abundance (ORA) = 3.0%) and Candidatus_Caldatribacterium (ORA = 1.7%) were found to be the key archaea and bacteria, respectively. Furthermore, the prediction of key microorganisms based on environmental factors and remaining microbial data showed the essential roles of Methanothermobacter and Acetomicrobium. The third layer for finding the optimal combination of data variables for predicting biogas production demonstrated that combined Archaea genera and environmental factors should be achieved for the most accurate prediction (root mean square error (RMSE) = 84.21). GBM had the best model performance and prediction accuracy among all the built-in models. Based on the optimal GBM model, the analysis at the system level showed that HRT was the most important variable. However the most important microorganism, Methanocelleus, within the appropriate survival range is also essential to achieve optimal biogas production. This research explores key parameters at various levels through automated machine learning techniques, which are expected to provide guidance in understanding the complex architecture of industrial and laboratory AD systems.
Authors
Simon BergAbstract
No abstract has been registered
Authors
Johannes BreidenbachAbstract
No abstract has been registered
Authors
Philip van Niekerk Gry Alfredsen Targo Kalamees Roja Modaresi Anna Sandak Jonas Niklewski Christian BrischkeAbstract
No abstract has been registered
Abstract
No abstract has been registered
Authors
Zeinab Qazanfarzadeh Abirami Ramu Ganesan Loredana Mariniello Lorenza Conterno Vignesh KumaravelAbstract
The accumulation of petroleum-based plastics causes economic and environmental concerns which necessitate a comprehensive search for biodegradable packaging materials. Brewer's spent grain (BSG) is an interesting by-product, which is one of the main wastes of beer production in Europe. BSG could offer added value in the food packaging sector owing to the significant amount generated annually, high biomaterials content, and low market value. Herein, the significance of various biorefinery techniques (physical, chemical, and biological) for the extraction of high-value products (such as protein, cellulose, hemicellulose, lignin, and phenolic compounds) from the BSG are comprehensively examined. BSG-derived biodegradable films and coatings for food packaging are critically evaluated. Finally, techno-economics, environmental impacts, energy consumption, regulations, challenges, and prospects are also critically evaluated. The best biorefinery system necessitates a balance between extraction efficiency, energy consumption, environmental impact, tangible upscaling, and operating cost. The mechanical dewatering of BSG before extraction, including the physical pretreatments, utilization of green solvents, the integration of the solvent recovery system, and the combination of two or more biorefinery techniques could reduce the energy requirements, greenhouse gas emissions, and increase the recovery yield of biomaterials. Cellulose, lignin, xylitol, and arabinoxylan are recommended as the most promising components from BSG for food packaging applications.
Authors
Michel VerheulAbstract
No abstract has been registered
Authors
Michel VerheulAbstract
No abstract has been registered
Abstract
Elymus repens is a problematic perennial weed in annual crops, grasslands and leys. Rhizome fragmentation by vertical disking can potentially reduce E. repens abundance with minimal tillage, but data are lacking on its efficiency in forage production. In a two-year study (2017–2018, 2018–2019) conducted in two forage grass-clover leys that were mostly weed-free except for large E. repens populations, this study examined effects on forage yield, botanical composition, and E. repens rhizome biomass of rhizome fragmentation at significant growth initiation in spring (early rhizome fragmentation, ERF) and/or when conditions allowed after the first forage cut (late rhizome fragmentation, LRF). Cold, wet springs and hard, dry soil in summer delayed treatment in both treatment years, to late spring (ERF) and late summer/early autumn (LRF). In the treatment year, ERF reduced first-cut forage yield by 44% compared with no rhizome fragmentation, while LRF decreased second- and third-cut yield by 24% and 53%, respectively. In the year after treatment, ERF increased total forage yield by on average 10%, while LRF had no effect. Over both years, combined forage yield was reduced by 11% by ERF and 4% by LRF. Both treatments reduced E. repens rhizome biomass, but inconsistently (ERF by 25% in one year only, LRF by 24% at one of two sites). ERF reduced E. repens incidence in forage by 10% in the treatment year, but had no effect in the following year. Thus, rhizome fragmentation by vertical disking can reduce E. repens abundance in grass-clover leys, but the effect is inconsistent and forage yield can be impaired, especially in swards with much E. repens. Moreover, disking is hampered by hard, dry soil conditions.
Abstract
No abstract has been registered