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
Abstract
Active crop sensor-based precision nitrogen (N) management can significantly improve N use efficiency but generally does not increase crop yield. The objective of this research was to develop and evaluate an active canopy sensor-based precision rice management system in terms of grain yield and quality, N use efficiency, and lodging resistance as compared with farmer practice, regional optimum rice management system recommended by the extension service, and a chlorophyll meter-based precision rice management system. Two field experiments were conducted from 2011 to 2013 at Jiansanjiang Experiment Station of China Agricultural University in Heilongjiang, China, involving four rice management systems and two varieties (Kongyu 131 and Longjing 21). The results indicated that the canopy sensor-based precision rice management system significantly increased rice grain yield (by 9.4–13.5%) over the farmer practice while improving N use efficiency, grain quality, and lodging resistance. Compared with the already optimized regional optimum rice management system, in the cool weather year of 2011, the developed system decreased the N rate applied in Kongyu 131 by 12% and improved N use efficiency without inducing yield loss. In the warm weather year of 2013, the canopy sensor-based management system recommended an 8% higher N rate to be applied in Longjing 21 than the regional optimum rice management, which improved rice panicle number per unit area and eventually led to increased grain yield by over 10% and improved N use efficiency. More studies are needed to further test the developed active canopy sensor-based precision rice management system under more diverse on-farm conditions and further improve it using unmanned aerial vehicle or satellite remote sensing technologies for large-scale applications.
Abstract
Accurate and non-destructive diagnosis of crop nitrogen (N) surplus and deficit status based on N nutrition index (NNI) is crucially important for the success of precision N management to improve N use efficiency (NUE) and reduce negative environmental impacts. However, due to the variability of the reflectance data obtained from different active crop sensors and complexity of the environmental and management conditions for regional applications, accurate determination of crop N status and topdressing N rate only using active canopy sensor data is very challenging. The objectives of this study were to (1) develop an in-season N status diagnosis and recommendation model based on NNI prediction using multi-source data fusion with machine learning, and (2) evaluate the accuracy of N diagnosis and recommendation in terms of rice yield and NUE under diverse on-farm conditions. Thirty plot experiments and thirteen on-farm experiments were conducted in Qixing Farm, Jiansanjiang, Northeast China from 2008 to 2018, and the dataset was used for the model calibration, validation, and evaluation. Two indirect and one direct NNI prediction methods using simple regression, stepwise multiple linear regression (SMLR) and random forest regression (RFR) were compared for N diagnosis and then integrated into N recommendation model. The results indicated that combining environmental and agronomic variables with crop sensor data improved the SMLR and RFR model performance by 1–16% and 9–40% over the corresponding models only using crop sensor data, respectively. The direct NNI prediction approach achieved slightly better N status diagnostic accuracy (areal agreement = 84% and Kappa statistics = 0.71) than indirect NNI prediction strategies based on plant N uptake and ΔN estimation (areal agreement = 81% and Kappa statistics = 0.67) or aboveground biomass and plant N uptake estimation (areal agreement = 77% and Kappa statistics = 0.58) across plot experiments and diverse on-farm conditions, based on multi-source data fusion with random forest regression models. About 82% of recommended N rates by the developed integrated in-season rice N diagnosis and recommendation model were within ±10 kg ha−1 of the measured economic optimum N rate across different varieties, environmental conditions and transplanting densities. Precision rice management based on in-season N diagnosis and recommendation decreased N rates and increased N partial factor productivity (PFPN) by 23% over regional optimum rice management, and significantly increased yield (7–11%) and PFPN (33–77%) over farmer's management. More studies are needed to develop in-season N diagnosis and recommendation strategies for applications across different regions and combine them with integrated precision rice management strategies for food security and sustainable development.
Authors
Krzysztof KusnierekAbstract
No abstract has been registered
Authors
Ingunn ØvsthusAbstract
No abstract has been registered
Abstract
Digestate, a by-product from anaerobic digestion of organic materials such as animal manure, is considered a suitable plant fertilizer. However, due to its bulkiness and low economic value, it is costly to transport over long distances and store for long periods. Refinement processes to valorize digestate and facilitate its handling as a fertilizer include precipitation of phosphorus-rich mineral compounds, such as struvite and calcium phosphates, membrane filtration methods that concentrate plant nutrients in organic products, and carbonization processes. However, phosphorus retention efficiency in output products from these processes can vary considerably depending on technological settings and characteristics of the digestate feedstock. The effects of phosphorus in plant fertilizers (including those analogous or comparable to refined digestate products) on agronomic productivity have been evaluated in multiple experiments. In this review, we synthesized knowledge about different refinement methods for manure-based digestate as a means to produce phosphorus fertilizers, thereby providing the potential to increase phosphorus retention in the food production chain, by combining information about phosphorus flows in digestate refinement studies and agronomic fertilizer studies. It was also sought to identify the range, uncertainty, and potential retention efficiency by agricultural crops of the original phosphorus amount in manure-based digestate. Refinement chains with solid/wet phase separation followed by struvite or calcium phosphate precipitation or membrane filtration of the wet phase and carbonization treatments of the solid phase were included. Several methods with high potential to extract phosphorus from manure-based wet phase digestate in such a way that it could be used as an efficient plant fertilizer were identified, with struvite precipitation being the most promising method. Synthesis of results from digestate refinement studies and agronomic fertilizer experiments did not support the hypothesis that solid/wet separation followed by struvite precipitation, or any other refinement combination, results in higher phosphorus retention than found for unrefined digestate. Further studies are needed on the use of the phosphorus in the solid phase digestate, primarily on phosphorus-rich soils representative of animal-dense regions, to increase understanding of the role of digestate refinement (particularly struvite precipitation) in phosphorus recycling in agricultural systems.
Authors
Ingunn ØvsthusAbstract
No abstract has been registered
Authors
Ingunn Øvsthus Mats Carlehög Guillaume Antalick Mitja Martelanc Tatjana Radovanovic Vukajlovic Lorena Butinar Melita, Sternad Lemut Branka, Mozetic VodopivecAbstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
The large brown seaweeds (kelps) are potential sources of protein for animal feed. They have lower protein contents than most red and green algae, but due to potential for large-scale production, they may represent a significant future protein source. The impact of pH, temperature and polysaccharide-degrading enzymes on the solubility and extraction yields of protein from wet Saccharina latissima biomass was investigated. The protein solubility increased with increasing pH and reached maximum of 23% at pH 11, determined as total amino acids (TAA). The enzyme treatments increased the release of soluble compounds by 30–35%. The highest protein yield obtained was 19%, using a ratio of water to wet seaweed of 1:1 for extraction. Even if the yields can be increased by increasing the water amounts used for extraction, the majority of the protein would remain in the insoluble residue after separation. The strategy for production of a larger quantity of protein-enriched biomass was therefore to maintain the insoluble fraction as the product. A pilot scale production was carried out, also including the red algae Palmaria palmata. In total 750 kg S. latissima and 195 kg P. palmata were processed. The protein content in the product increased from 10 to 20% of dry weight (dw) for S. latissima and from 12 to 28% for P. palmata, with yields of 79 and 69%, respectively. The ash content was reduced from 44 to 26% and from 12 to 5% of dw, respectively, for the two species. The main protein loss was free amino acids, which constituted approximately 10% of TAA in the feedstocks. Less essential than non-essential amino acids were lost, thus, the essential amino acids were enriched in the product.
Abstract
Kelp forests in the North Atlantic are at risk of decline at their warm temperature distribution margins due to anthropogenic temperature rise and more frequent marine heat waves. To investigate the thermal adaptation of the cold-temperate kelp Laminaria digitata, we sampled six populations, from the Arctic to Brittany (Spitsbergen, Tromsø, Bodø [all Norway], Helgoland [Germany], Roscoff and Quiberon [both France]), across the species’ entire distribution range, spanning 31.5° latitude and 12-13°C difference in mean summer sea surface temperature. We used pooled vegetative gametophytes derived from several sporophytes to approximate the genetic diversity of each location. Gametophytes were exposed to (sub-) lethal high (20-25°C) and (sub-) optimal low (0-15°C) temperature gradients in two full-factorial, common-garden experiments, subjecting subsets of populations from different origins to the same conditions. We assessed survival of gametophytes, their ability to develop microscopic sporophytes, and subsequent growth. We hypothesized that the thermal performance of gametophytes and microscopic sporophytes corresponds to their local long-term thermal history. Integrated gametophyte survival revealed a uniform upper survival temperature (UST) of 24°C among five tested populations (Tromsø to Quiberon). In contrast, following two weeks of thermal priming of gametophytes at 20-22°C, sporophyte formation at 15°C was significantly higher in southern populations (Quiberon and Roscoff) compared to the high-latitude population of Tromsø. Between 0-15°C, survival of the Arctic population (Spitsbergen) was negatively correlated with increasing temperatures, while the southern-most population (Quiberon) showed the opposite. Thus, responses of survival at low, and sporophyte formation at high temperatures, support the concept of local adaption. On the other hand, sporophyte formation between 0-15°C peaked at 6-9°C in the Quiberon and at 9-12°C in the Spitsbergen population. Sporophyte growth rates (GR) both in length and width were similar for Spitsbergen, Tromsø and Quiberon; all had maximum GRs at 12-15°C and low GRs at 0-6°C. Therefore, responses of sporophyte formation and growth at low temperatures do not reflect ecotypic adaptation. We conclude that L. digitata populations display trait-dependent adaptation, partly corresponding to their local temperature histories and partly manifesting uniform or unpredictable responses. This suggests differential selection pressures on the ontogenetic development of kelps such as L. digitata.