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.

2019

To document

Abstract

The nitrogen cycle has been radically changed by human activities1 . China consumes nearly one third of the world’s nitrogen fertilizers. The excessive application of fertilizers2,3 and increased nitrogen discharge from livestock, domestic and industrial sources have resulted in pervasive water pollution. Quantifying a nitrogen ‘boundary’4 in heterogeneous environments is important for the effective management of local water quality. Here we use a combination of water-quality observations and simulated nitrogen discharge from agricultural and other sources to estimate spatial patterns of nitrogen discharge into water bodies across China from 1955 to 2014. We find that the critical surface-water quality standard (1.0 milligrams of nitrogen per litre) was being exceeded in most provinces by the mid-1980s, and that current rates of anthropogenic nitrogen discharge (14.5 ± 3.1 megatonnes of nitrogen per year) to fresh water are about 2.7 times the estimated ‘safe’ nitrogen discharge threshold (5.2 ± 0.7 megatonnes of nitrogen per year). Current efforts to reduce pollution through wastewater treatment and by improving cropland nitrogen management can partially remedy this situation. Domestic wastewater treatment has helped to reduce net discharge by 0.7 ± 0.1 megatonnes in 2014, but at high monetary and energy costs. Improved cropland nitrogen management could remove another 2.3 ± 0.3 megatonnes of nitrogen per year—about 25 per cent of the excess discharge to fresh water. Successfully restoring a clean water environment in China will further require transformational changes to boost the national nutrient recycling rate from its current average of 36 per cent to about 87 per cent, which is a level typical of traditional Chinese agriculture. Although ambitious, such a high level of nitrogen recycling is technologically achievable at an estimated capital cost of approximately 100 billion US dollars and operating costs of 18–29 billion US dollars per year, and could provide co-benefits such as recycled wastewater for crop irrigation and improved environmental quality and ecosystem services.

To document

Abstract

We studied the effect of threePandora neoaphidisisolates from oneSitobion avenaepopulation, threetemperatures, and two aphid species namelyS. avenae and Rhopalosiphum padion (i) aphid mortality, (ii)time needed to kill aphids, and (iii) aphid average daily and lifetime fecundity. A total of 38% ofS. avenaeand 7% ofR. padidied and supported fungus sporulation.S. avenaewas killed 30% faster thanR. padi.Average daily fecundity was negatively affected only inS. avenaeinoculated with, but not killed by,P. neoaphidis. Nevertheless, lifetime fecundity of both aphid species inoculated and sporulating withP. neoaphidiswas halved compared to lifetime fecundity of surviving aphids in the control. Increasedtemperature resulted in higher mortality rates but did not consistently affect lethal time or fecundity.Results suggest that (i) temperature effects on virulence differ between isolates, even when obtainedwithin the same host population, and (ii) even though an isolate does not kill a host it may reduce itsfecundity. Ourfindings are important for the understanding ofP. neoaphidisepizootiology and for use inpest-natural enemy modelling.

To document

Abstract

Red clover (Trifolium pratense) grown in mixtures with grasses often constitutes a lower proportion of total yield in spring than in summer growth. A more even red clover proportion between the harvests would benefit forage quality and management at feeding. We investigated whether inclusion of early versus late‐maturing red clover varieties could reduce this disproportionality. In a two‐year field trial harvested three times per season, each of six red clover varieties was grown in two grass mixtures. Rate of phenological development did not differ during spring growth, but did so in regrowth after first and second cuts. Here, the earliest varieties constituted the highest proportion. At all harvests, the early varieties had lower crude protein concentrations and a higher content of neutral detergent fibre (NDF) and indigestible NDF than the late varieties. Clover proportion was higher in swards with a mixture of timothy and meadow fescue than in swards with perennial ryegrass during the first year and lower in the second year. It is concluded that developmental rate should be explored further as a key character for red clover competiveness in spring growth of rapidly elongating grasses.

Abstract

The objective of this paper was to examine how cutting frequency, silage fermentation patterns and clover performance in grass-clover swards influence the use of inputs and profitability in an organic dairy system. A linear programming model was developed to compare a three-cut and a two-cut system for a model farm in Central Norway, either with restricted or extensive silage fermentation at low or high red clover (Trifolium pratense L.) proportion in the sward, giving 8 different silage types in all. Input-output relations incorporated into the model were derived from a meta-analysis of organic grassland field trials in Norway as well as a silage fermentation experiment, and with feed intakes and milk yields from simulations with the ‘TINE Optifôr’ feed ration planner in the Norfor feed evaluation system. The model maximized total gross margin of farms with 260,000 l milk quota and housing capacity for 45 cows, with separate model versions for each of the 8 silage types. Farmland availability varied from 30 to 70 ha with 40 ha as the basis. Our results suggested that farmland availability and marginal return of a competing barley crop profoundly influenced the profitability of the different silage types. A high clover proportion increased dry matter (DM) yields and was far more important for profitability than the score on the other factors considered at restricted land availabilities. Profits with the three-cut systems were always greater than those with the two-cut systems, the former being associated with greater silage intakes and improved dairy cow performances but lower DM forage yields. Three-cut systems were further favoured as land availability increased and also by a lower marginal return of barley. Although use of an acidifying silage additive improved feed intakes and milk production per cow, the practice reduced total milk production and depressed profit compared to untreated, extensively fermented silage at restrictive land availabilities. With more land available, and in particular at a low marginal return of barley, use of a silage additive was profitable.

2018

Abstract

The key factor for autonomous navigation is efficient perception of the surroundings,while being able to move safely from an initial to a final point. We deal in this paper with a wheeled mobile robot working in a GPS-denied environment typical for a greenhouse. The Hector Simultaneous Localization and Mapping (SLAM) approach is used in order to estimate the robots’ pose using a LIght Detection And Ranging (LIDAR) sensor. Waypoint following and obstacle avoidance are ensured by means of a new artificial potential field (APF) controller presented in this paper. The combination of the Hector SLAMand the APF controller allows themobile robot to performperiodic tasks that require autonomous navigation between predefined waypoints. It also provides themobile robot with a robustness to changing conditions thatmay occur inside the greenhouse, caused by the dynamic of plant development through the season. In this study, we show that the robot is safe to operate autonomously with a human presence, and that in contrast to classical odometrymethods, no calibration is needed for repositioning the robot over repetitive runs. We include here both hardware and software descriptions, as well as simulation and experimental results.

To document

Abstract

Crop models are widely used to evaluate the response of crop growth to drought. However, over large geographic regions, the most advanced models are often restricted by available computing resource. This limits capacity to undertake uncertainty analysis and prohibits the use of models in real-time ensemble forecasting systems. This study addresses these concerns by presenting an integrated system for the dynamic prediction and assessment of agricultural yield using the top-ranked Sunway TaihuLight supercomputer platform. This system enables parallelization and acceleration for the existing AquaCrop, DNDC (DeNitrification and DeComposition) and SWAP (Soil Water Atmosphere Plant) models, thus facilitating multi-model ensemble and parameter optimization and subsequent drought risk analysis in multiple regions and at multiple scales. The high computing capability also opens up the possibility of real-time simulation during droughts, providing the basis for more effective drought management. Initial testing with varying core group numbers shows that computation time can be reduced by between 2.6 and 3.6 times. Based on the powerful computing capacity, a county-level model parameter optimization (2043 counties for 1996–2007) by Bayesian inference and multi-model ensemble using BMA (Bayesian Model Average) method were performed, demonstrating the enhancements in predictive accuracy that can be achieved. An application of this system is presented predicting the impacts of the drought of May–July 2017 on maize yield in North and Northeast China. The spatial variability in yield losses is presented demonstrating new capability to provide high resolution information with associated uncertainty estimates.

To document

Abstract

Precipitation is an important source of soil water, which is critical to crop growth, and is therefore an important input when modelling crop growth. Although advances are continually being made in predicting and recording precipitation, input uncertainty of precipitation data is likely to influence the robustness of parameter estimate and thus the predictive accuracy in soil water and crop modelling. In this study, we use the Bayesian total error analysis (BATEA) method for the water-oriented crop model AquaCrop to identify the input uncertainty from multiple precipitation products respectively, including gauge-corrected grid dataset CPC, remote sensing based TRMM and reanalysis based ERA-Interim. This methodology uses latent variables to correct the input data errors. Adopting a single-multiplier method for precipitation correction, we simulate maize growth in both field and regional levels in China for a range of different possible climatic scenarios. Meanwhile, we use the average of multiple products for model driving in comparison. The results show that the BATEA method can consistently reduce uncertainty for crop growth prediction among different precipitation products. In regional simulation, the improvements for the three products are 1%, 7.3% and 2.8% on average in drought scenarios. These results imply the BATEA approach can be of great assistance for crop modeling studies and agricultural assessments under future changing climates.