In geometric morphometrics, the extent of variation attributable to non-biological causes (i.e. measurement error) is sometimes overlooked. The effects of this variation on downstream statistical analyses are also largely unknown. In particular, it is unclear whether specimen preservation induces substantial variation in shape and whether such variation affects downstream statistical inference. Using a combination of empirical fish body shape data and realistic simulations, we show that preservation introduces substantial artefactual variation and significant non-random error (i.e. bias). Most changes in shape occur when fresh fish are frozen and thawed, whereas a smaller change in shape is observed when frozen and thawed fish are fixed in formalin and transferred to ethanol. Surprisingly, we also show that, in our case, preservation produces only minor effects on three downstream analyses of shape variation: classification using canonical variate analysis, permutation tests of differences in means and computations of differences in mean shape between groups. Even mixing of differently preserved specimens has a relatively small effect on downstream analyses. However, we suggest that mixing fish with different preservation should still be avoided and discuss the conditions in which this practice might be justified.
1 September 2021 in Agricultural and Forest Meteorology
Fluctuating asymmetry in plant leaves is a widely used measure in geometric morphometrics for assessing random deviations from perfect symmetry. In this study, we considered the concept of fluctuating asymmetry to improve the prototype leaf shape of the functional-structural plant model L-Cucumber. The overall objective was to provide a realistic geometric representation of the leaves for the light sensitive plant reactions in the virtual plant model. Based on three-dimensional data from several hundred in situ digitized cucumber leaves comparisons of model leaves and measurements were conducted. Robust Bayesian comparison of groups was used to assess statistical differences between leaf halves while respecting fluctuating asymmetries. Results indicated almost no directional asymmetry in leaves comparing different distances from the prototype while detecting systematic deviations shared by both halves. This information was successfully included in an improved leaf prototype and implemented in the virtual plant model L-Cucumber. Comparative virtual plant simulations revealed a slight improvement in plant internode development against experimental data using the novel leaf shape. Further studies can now focus on analyses of stress on the 3D-deformation of the leaf and the development of a dynamic leaf shape model.
Sunburn in grapevine berries is known as a recurring disorder causing severe yield losses and a decline in berry quality. The transition from healthy to sunburnt along a temporal trajectory is not fully understood. It is driven by light-boosted local heat impact and modulated by, e.g., past environments of the berry and its developmental state. Events of berry sunburn are often associated with heatwaves, indicating a link to climate change. In addition, the sensitivity of grapevine architecture to changing environmental condition indicates an urgent need to investigate and adapt mitigation strategies of berry sunburn in future vineyards. In this perspective, we want to identify missing links in predicting berry sunburn in vineyards and propose a modeling framework that may help us to investigate berry sunburn in future vineyards. For this, we propose to address open issues in both developing a model of berry sunburn and considering dynamic canopy growth, and canopy interaction with the environment and plant management such as shoot positioning or leaf removal. Because local environmental conditions drive sunburn, we aim at showing that identifying sunburn-reducing strategies in a vineyard under future environmental conditions can be supported by a modeling approach that integrates effects of management practices over time and takes grapevine architecture explicitly into account. We argue that functional-structural plant models may address such complex tasks. Once open issues are solved, they might be a promising tool to advance our knowledge on reducing risks of berry sunburnin silico.
Challenges of climate change on the future grape and wine production are widely discussed in science and in the wine industry with the goal to maintain a consistent must and wine quality in the future. Therefore, the effect of elevated CO2 (eCO2)—as one of the relevant greenhouse gases jointly responsible for a changing climate—was investigated concerning the composition of must and wine made of two grapevine cultivars V. vinifera L. cvs. Riesling and Cabernet Sauvignon within the established VineyardFACE (Free-Air Carbon dioxide Enrichment) experiment. Must and wine analysis were conducted in three consecutive years (2014–2016) by analyzing standard must and wine parameters, e.g., total soluble solids (TSS), pH, total acidity (TA), organic acids (e.g., tartaric acid, malic acid, shikimic acid, citric acid, volatile acid and gluconic acid) or total phenolics (TP). Also, for both cultivars CIELab coordinates (L* for lightness, a* as green/red and b* as blue/yellow components) were used to test colour in young white and red wines. Additionally, total anthocyanins and monomeric indices were analyzed for young wines of the red cultivar Cabernet Sauvignon. With marginal differences between CO2 treatments, the composition of must and young wines was not found to be negatively influenced by an eCO2 concentration.
Future climatic conditions might have severe effects on grapevine architecture, which will be highly relevant for vineyard management decisions on shoot positioning, pruning or cutting. This study was designed to help gaining insight into how, in particular, increasing temperatures might affect grapevine canopies. We developed a functional-structural model for Riesling, Virtual Riesling, based on digitised data of real plants and a comprehensive state-of-the-art data analysis. The model accounts for the variability in temperature-sensitive morphological processes, such as bud break and appearance rates. Our simulation study using historical weather data revealed significant effects of the thermal time course over the year on bud burst of the cane and on primary shoots. High variabilities in these events affect canopy growth and leaf area distribution. This report shows that Virtual Riesling can be useful in assessing the significance of changing temperatures for grapevine architecture and thereby considering management techniques such as vertical shoot positioning. Further developments of Virtual Riesling might support the knowledge gain for developing necessary adaptations in future vineyard management and, thus, facilitate future work on climate change research using functional-structural model approaches.