Newest publications
Bayesian A-optimal two-phase designs with a single blocking factor in each phase
(2023) Vo-Thanh, Nha; Piepho, Hans-Peter
Two-phase experiments are widely used in many areas of science (e.g., agriculture, industrial engineering, food processing, etc.). For example, consider a two-phase experiment in plant breeding. Often, the first phase of this experiment is run in a field involving several blocks. The samples obtained from the first phase are then analyzed in several machines (or days, etc.) in a laboratory in the second phase. There might be field-block-to-field-block and machine-to-machine (or day-to-day, etc.) variation. Thus, it is practical to consider these sources of variation as blocking factors. Clearly, there are two possible strategies to analyze this kind of two-phase experiment, i.e., blocks are treated as fixed or random. While there are a few studies regarding fixed block effects, there are still a limited number of studies with random block effects and when information of block effects is uncertain. Hence, it is beneficial to consider a Bayesian approach to design for such an experiment, which is the main goal of this work. In this paper, we construct a design for a two-phase experiment that has a single treatment factor, a single blocking factor in each phase, and a response that can only be observed in the second phase.
Lithium chloride leads to concentration dependent brood damages in honey bee hives (Apis mellifera) during control of the mite Varroa destructor
(2022) Rein, Carolin; Makosch, Marisa; Renz, Julia; Rosenkranz, Peter
Lithium chloride (LiCl) has a high efficacy against Varroa destructor and a good tolerability for adult bees but the effect of LiCl on the honey bee brood has not been taken into consideration yet. We quantified the mortality of larvae fed with different concentrations of LiCl. For artificially reared larvae already, a concentration of 1 mM had significant toxic effects while under colony conditions, 10 mM was well tolerated. However, a chronic application of the effective concentration of 25 mM elicited brood mortalities between 60 and 90%. Shorter feeding periods of 2 or 4 days reduced the brood damages significantly. Measurements of the lithium concentrations in larvae and pupae during a chronic exposure with 10, 17.5 and 25 mM LiCl revealed respective lithium levels in 5th instar larvae of 7, 13 and 15 mg/kg. No lithium was detectable in 2-day old larvae indicating that pure worker jelly from the hypopharyngeal gland is not contaminated with LiCl. Based on these results, applications of LiCl in colonies with brood should be avoided.
Tackling foam-based process disruptions in spirit distillation by thermal energy input adaptations
(2022) Heller, Daniel; Roj, Simon; Switulla, Julia; Kölling, Ralf; Einfalt, Daniel
Process impairing foam formation occurs regularly in batch distillation devices of the spirit industry. It negatively influences process and product quality. Up to now, such foam-related problems have not been in the focus of scientific investigations. This study aimed at preventing impairing foam formations by adapting the thermal energy input in fruit and grain mash distillations in larger scale batch distillations. The results showed that a reduction of the thermal energy input to 43 ± 1 W·L −1 during the initial heating of the mash leads to less flooding of the distillation apparatus and to a higher concentration of lower boiling compounds like methanol, acetaldehyde, and ethyl acetate as well as ethanol in the first fractions of the distillates. A standard process time and less energy consumption could be achieved by increasing the energy input again after prior reduction. However, this led to a reduction of the ethanol concentration in the distillate fractions of up to 4.3%vol, also most severe in the first fractions. A significant influence on analyzed volatile compounds in the distillate besides ethanol could not be detected. This is the first study that uses defined thermal energy input adaptations for foam management in larger scale distillation devices. The results lead the way to a more efficient distillation process with less foam formation.
The value of remotely sensed vs. field-surveyed habitat structure for predicting bird abundance: a case study in traditional orchards
(2022) Chaparro, Laura; Schmieder, Klaus; Schurr, Frank M.
Understanding environmental effects on the distribution and abundance of species is central to ecology, biogeography and evolutionary biology. This led to the development of species distribution models (SDMs) that relate spatial variation in occurrence and abundance to environmental variables. So far, SDMs rarely considered habitat structure, as a major determinant of bird distributions. While remote sensing increasingly provides high-resolution measures of habitat structure, certain structural variables affecting bird abundance still need to be measured with field surveys. In this study, we compare the value of remotely sensed vs. field-surveyed habitat structure for predicting bird abundance. Specifically, we analysed abundance data for nine bird species of traditional orchards in South-Western Germany. ‘Remote sensing SDMs’ related abundance to structural variables obtained by aerial photogrammetry of individual orchard trees. Alternative ‘field survey SDMs’ related bird abundance to detailed field surveys of the species composition and pruning state of orchard trees. Additionally, both remote sensing and field survey SDMs included climate and land use variables. Accounting for detailed habitat structure improved abundance predictions for seven of nine study species compared to models only incorporating climate and land use. The impact on model performance differed between remotely sensed and field-surveyed variables: the former improved abundance models for most ( n = 7) bird species, whereas the latter had more variable impact, decreasing model performance for five species. The remotely sensed variable with strongest effects was overall tree density, which positively affected abundance of seven species. In contrast, multiple field-surveyed variables had similar effect strength, with the overall strongest effect found for pear tree density, to which seven bird species showed a unimodal response. These analyses have conservation implications since they predict expected responses of bird species to ongoing changes in orchard structure. Moreover, they identify structural variables that will be most promising to measure via remote sensing data in the future.
A multivariate approach to drought monitoring: Improving robustness and accuracy through a new drought index in regions with high climate variability, applied to the drought-prone region of Ethiopia
(2026) Kebede, Abebe; Warrach-Sagi, Kirsten; Schwitalla, Thomas; Wulfmeyer, Volker; Abebe, Tesfaye; Tadesse, Tsegaye
Study focus: Assessing, monitoring, and quantifying drought characteristics to develop early warning systems is crucial for identifying the spatial extent and severity of droughts at regional and local scales especially in regions of vulnerable societies relying on local agriculture. Observations and reanalysis from 1981 to 2022 are analyzed for spatiotemporal droughts in Ethiopia. While standard drought indices like Standardized Precipitation Index and Standardized Soil Moisture Index are based solely on precipitation or soil moisture, a new drought index based on precipitation, potential evaporation, surface temperature, soil temperature, and soil moisture is developed, making the index more robust to climate and land use changes. This new Multivariate Standardized Drought Index (MvrSDI) is evaluated focusing on the severity and duration of 2015 and 2022 droughts in Ethiopia. Results show that spatiotemporal comparisons of MvrSDI at 3-, 6-, and 12-month time scales detect drought severity and duration in each drought-prone region of Ethiopia. Further,Mann-Kendall statistic test identifiy a drought trend between 1981 and 2022 an increasing drought severity.
New hydrological insight for the region: The MvrSDI effectively assesses and monitors drought impacts on agriculture, proving beneficial for stakeholders focused on environmental sustainability and food security. Its multivariate character makes MvrSDI more robust and therefore a valuable tool for drought monitoring and decision-making in regions with high climate variability and land use changes in drought-prone regions like Ethiopia.