500 Naturwissenschaften
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Dairy farming has been the subject of public debate on animal welfare for a number of years now. Animal welfare discussions on dairy farming often include the demand for more nature connectedness in this area. This study focuses on the divergent perspectives of consumers and scientists on the importance of more nature connectedness for animal welfare strategies in German dairy farming. Within Europe, Germany is the main producer of cow’s milk and an important industry in many rural areas in Germany is dairy farming. The insights presented are based on qualitative interviews with dairy farming and livestock researchers from Germany and Austria. A key finding of this study is that we need to look more closely at the actual content of nature claims in animal welfare debates. The scientists interviewed tend to see idealized conditions in animal welfare discussions with images of nature which in fact seldom lead to improved conditions in dairy farming and, even then, only to a limited extent. The scientists interviewed rate calls for more nature connectedness in dairy farming from the nonagricultural public as anti-modern, complexity-reducing, and normative. Nevertheless, some of the scientists interviewed did have valuable insights into the nonagricultural public’s criticism of dairy farming practices. These scientists argued, however, that animal welfare needs to differentiate between nature connectedness and the innate needs of cattle when it comes to animal welfare strategies. An important conclusion of the study is that more discussion formats are needed to promote the exchange of ideas between different social groups attempting to understand animal welfare in dairy farming.
Hyperhydricity (HH) is one of the most important physiological disorders that negatively affects various plant tissue culture techniques. The objective of this study was to characterize optical features to allow an automated detection of HH. For this purpose, HH was induced in two plant species, apple and Arabidopsis thaliana, and the severity was quantified based on visual scoring and determination of apoplastic liquid volume. The comparison between the HH score and the apoplastic liquid volume revealed a significant correlation, but different response dynamics. Corresponding leaf reflectance spectra were collected and different approaches of spectral analyses were evaluated for their ability to identify HH-specific wavelengths. Statistical analysis of raw spectra showed significantly lower reflection of hyperhydric leaves in the VIS, NIR and SWIR region. Application of the continuum removal hull method to raw spectra identified HH-specific absorption features over time and major absorption peaks at 980 nm, 1150 nm, 1400 nm, 1520 nm, 1780 nm and 1930 nm for the various conducted experiments. Machine learning (ML) model spot checking specified the support vector machine to be most suited for classification of hyperhydric explants, with a test accuracy of 85% outperforming traditional classification via vegetation index with 63% test accuracy and the other ML models tested. Investigations on the predictor importance revealed 1950 nm, 1445 nm in SWIR region and 415 nm in the VIS region to be most important for classification. The validity of the developed spectral classifier was tested on an available hyperspectral image acquisition in the SWIR-region.
Methods: Systematic review of randomized controlled trials (RCT). Searches were conducted in five electronic databases. Studies were selected if they included patients with NP over 18 years old treated with aerobic exercise (AE) (e.g., cycling, running, hiking, and walking). The main outcome of interest was pain intensity. Qualitative and quantitative data were extracted. The risk of bias (RoB) was determined using the Cochrane RoB Tool-2 and the overall certainty of the evidence with the GRADE recommendations.
Results: Out of 21,585 initial records screened, a total of six individual studies published in ten manuscripts were included. There was a great heterogeneity between protocols, comparisons, and studies’ results (different magnitudes and directions). When looking at the effect of aerobic exercise versus control groups or other interventions on pain intensity measured with the VAS, not statistically (nor clinical) significant differences between aerobic exercise and control groups (MD [95%CI] 5.16 mm [-6.38, 16.70]) were identified. The combined effect of AE plus other interventions seems to be effective. Strength exercise obtained better effects than aerobic exercises (MD [95%CI]: -11.34 mm [-21.6, -1.09]).
Conclusions: Aerobic exercise presented positive results to reduce pain intensity, and improving disability, and physical and emotional functioning. However, the evidence is restricted, low quality, and heterogeneous.
Within the consortium “Experimentation Field Agro-Nordwest”, a practical concept for knowledge and technology transfer of digital competence in agriculture was created. For this purpose, the web-based e-learning system “SensX” was set up, consisting of videos, presentations and instructions. In addition, the classical e-learning concept was extended by data sets, student experiments and sensor data of plants acquired by a remote phenotyping robot. This resulted in a massive open online course (MOOC), which was tested with agricultural and biotechnology students in higher education at the University of Applied Sciences Osnabrück over two years. The evaluation process of “SensX” included an empirical survey, qualitative interviews of the participating students by an external institution and an evaluation of the concept by the lecturers.
Recording of Low-Oxygen Stress Response Using Chlorophyll Fluorescence Kinetics in Apple Fruit
(2023)
Long-term storage of apples (Malus x domestica, Borkh.) is increasingly taking place under Dynamic Controlled Atmosphere (DCA). The oxygen level is lowered to ≤ 1 kPa O2 and the apples are stored just above the Lower Oxygen Limit (LOL). Low oxygen stress during controlled atmosphere storage can lead to fermentation in apples if oxygen levels are too low. Chlorophyll fluorescence can be used to detect low-oxygen stress at an early stage during storage. The currently available non-imaging fluorescence systems often use the minimal fluorescence (Fo) parameter. In contrast, the use of chlorophyll fluorescence kinetics is insufficiently described. Therefore, this study aimed to gain more knowledge about the response of chlorophyll fluorescence kinetics to low oxygen stress in apples using a fluorescence imaging system. The results show that the kinetic fluorescence curves differ under aerobic and fermentation conditions. The fermentative conditions initiated a decrease in fluorescence intensity upon application of the saturation pulses during exposure to actinic light. This result was made at 18 °C and 2 °C ambient temperatures. Interestingly, the kinetic curve changed at 2 °C before fermentation products accumulated in the apples. Non-photochemical quenching (NPQ) decreased under fermentation conditions in the dark phase after relaxation. Upon entering the dark relaxation phase after Kautsky induction, ɸPSII began to increase. Under atmospheric oxygen conditions, ɸPSII reached values of 0.81 to 0.76, while under fermentation, ɸPSII values ranged from 0.57 to 0.44.
Background
The current development of sensor technologies towards ever more cost-effective and powerful systems is steadily increasing the application of low-cost sensors in different horticultural sectors. In plant in vitro culture, as a fundamental technique for plant breeding and plant propagation, the majority of evaluation methods to describe the performance of these cultures are based on destructive approaches, limiting data to unique endpoint measurements. Therefore, a non-destructive phenotyping system capable of automated, continuous and objective quantification of in vitro plant traits is desirable.
Results
An automated low-cost multi-sensor system acquiring phenotypic data of plant in vitro cultures was developed and evaluated. Unique hardware and software components were selected to construct a xyz-scanning system with an adequate accuracy for consistent data acquisition. Relevant plant growth predictors, such as projected area of explants and average canopy height were determined employing multi-sensory imaging and various developmental processes could be monitored and documented. The validation of the RGB image segmentation pipeline using a random forest classifier revealed very strong correlation with manual pixel annotation. Depth imaging by a laser distance sensor of plant in vitro cultures enabled the description of the dynamic behavior of the average canopy height, the maximum plant height, but also the culture media height and volume. Projected plant area in depth data by RANSAC (random sample consensus) segmentation approach well matched the projected plant area by RGB image processing pipeline. In addition, a successful proof of concept for in situ spectral fluorescence monitoring was achieved and challenges of thermal imaging were documented. Potential use cases for the digital quantification of key performance parameters in research and commercial application are discussed.
Conclusion
The technical realization of “Phenomenon” allows phenotyping of plant in vitro cultures under highly challenging conditions and enables multi-sensory monitoring through closed vessels, ensuring the aseptic status of the cultures. Automated sensor application in plant tissue culture promises great potential for a non-destructive growth analysis enhancing commercial propagation as well as enabling research with novel digital parameters recorded over time.