Putting two water transport models to the test under wet and dry conditions

In order to improve fruit quality and quantity, accurate monitoring of the water status is necessary. The water status can be continuously predicted by using a mechanistic water transport and storage model (e.g. Steppe et al., 2006; 2008). This model typically links measurements of sap flow rate (SF) and stem diameter variations (D) to simulate stem water potential (Ψstem), which is recognised as one of the best indicators for evaluating plant water status. Despite good model performance under sufficient water availability, the model fails under dry conditions. However, a proper simulation of water transport under drought is essential for many applications. For example, grapevines are often subjected to some level of drought stress during the growing season in order to improve the quality of the grapes. Therefore, we aim at adjusting the existing model to improve its performance in simulating water transport during drought conditions. First, a dynamic function describing changes in hydraulic xylem resistance is used to replace the former constant parameter, and represents the resistances encountered in the soil, root and stem (RX). Second, also the former constant radial flow resistance between xylem and storage tissues has been replaced by an equation (RS). For the first time, equations for RX and RS instead of parameters were used in the model, and simulations were compared to the original ones. Both models functioned well under wet conditions, but where the original model failed under dry events, the adapted model could still accurately simulate D and Ψstem under these conditions. The adapted model is thus capable of describing the grapevine’s hydraulic response to both wet and (severe) drought conditions and seems very promising within the context of an automatic plant-based system for water status monitoring

Development of a plant-based strategy for water status monitoring and stress detection in grapevine

Water shortage has become a major problem, leading to a growing interest for efficient and precise irrigation scheduling even in areas that were completely rain-fed so far. Appropriate irrigation for grapevines (Vitis vinifera L.) is not exclusively a story of fulfilling water demand, but rather of defining the optimum level and timing and having a good knowledge of the grapevine water status. Specific levels of soil water deficit at specific times in the growing season are known to play a key role in the production of high quality grapes and resulting wines, but both severe and no drought stress are not desired as they negatively influence the grape’s and wine’s potential. Innovative techniques for monitoring the plant water status and for applying an adequate irrigation scheduling are required to achieve this crucial water balance for a grapevine. It is internationally recognised that such tools should rely on plant measurements, as they provide information on the actual plant water status, rather than be based on soil or microclimatic measurements. The aim of this thesis was to develop and evaluate a strategy for water status monitoring and stress detection in grapevine based on automated plant measurements. To this end, both experimental and modelling work was carried out on potted grapevines that were subjected to conditions ranging from fully irrigated to severe drought. Two different plant-based monitoring approaches were tested and compared. In a first approach, an accurate monitoring of the grapevine water status and a fast detection of drought stress (i.e. several days before the first clear visible symptoms appeared) were accomplished using two data-driven models: Unfold Principle Component Analysis (UPCA) and Functional Unfold Principle Component Analysis (FUPCA). These models were originally developed for statistical process monitoring of multivariate data sets where accurate mechanistic knowledge is lacking or difficult to achieve. In this study, the multivariate data set consisted of measured microclimatic variables and a plant measurement that served as indicator for plant water status, either sap flow rate or stem diameter variations. Using a large amount of data from well-watered conditions, the models extracted the information and patterns underlying these measured variables and made a profile of normal, expected data behaviour under sufficient water availability. Monitoring new data then implied checking these data against this pattern. When a discrepancy between new data and this normal pattern was observed, the models indicated abnormality, which was in this study related to a deviating water status or drought stress. Unlike the data-driven approach in which a priori information on underlying plant mechanisms was not crucial, the second approach focused on developing a comprehensive mechanistic water transport and storage model for grapevine. This mechanistic model mathematically describes the axial and radial water transport and stem diameter dynamics of grapevine. The basic principles originated from an existing tree water transport and storage model, which enabled among others accurate simulations of the stem water potential (Ψstem) under well-watered conditions, which is one of the best indicators for plant water status. To obtain better drought response simulations with the model, the constant hydraulic plant resistances were replaced by equations in this PhD study. Both the integrated hydraulic resistance experienced during upward water transport through the soil-to-stem segment (RX) and the hydraulic resistance encountered during radial water transport between xylem and elastic living tissues (RS) were dependent on soil water potential. Modelled and measured data were compared to verify the implemented mechanisms. The mechanistic model was applied twofold. First, the model contributed to our understanding of grapevine functioning during drought conditions, as it revealed new insights. Despite the generally assumed constant RX and RS behaviour in several other plant models, the improved model demonstrated that both RX and RS showed daily fluctuations and, superimposed on these fluctuations, exponentially increased when drought progressed. Furthermore, it was shown that mean turgor in the elastic storage tissues rapidly decreased with drought. Finally, an in situ soil-to-stem vulnerability curve that integrated the hydraulic conductance in soil and plant (KX = 1/RX) was generated using the model. Such a curve depicts the loss in KX as a function of declining Ψstem and is often applied in the literature to assess vulnerability of species to drought. Second, the mechanistic model was elaborated as a tool to monitor grapevine water status in real-time. Except under most severe drought stress conditions, which are not favourable for grape and wine quality and should be avoided in practice, the model simulated Ψstem well and kept a tight supervision over the grapevine water status, as Ψstem could be continuously compared against expected plant behaviour defined under well-watered conditions. Simulated Ψstem, representing the actual water status of the grapevine, were then compared with a dynamic threshold beyond which the grapevine is considered to experience drought stress. In this study, the uncertainty band on the dynamic threshold estimation was used to represent the range within which Ψstem was expected to occur under well-watered conditions. Two different dynamic Ψstem thresholds were tested: an approach using vapour pressure deficit (VPD) as input, and a more elaborate approach using potential evapotranspiration (λEp). The latter includes VPD and radiation, both known as key driving variables for plant transpiration. The use of both the VPD- or the λEp-based dynamic threshold and uncertainty band allowed a fast detection of drought stress and tight supervision over the plant water status during a drought experiment on grapevines. To conclude, both the data-driven and the mechanistic modelling approach were judged promising as plant-based strategy for monitoring the grapevine water status. To apply these strategies for optimising grape and wine quality in practice, some challenges remain. As all experiments in this study were conducted on potted grapevines, future experiments should test the performance of the models under field conditions. In addition, the exact impact on the grape berries of different drought levels at specific times during the growing season should be investigated, in order to be able to steer grape and wine quality in the future

New type of vulnerability curve gives insight in the hydraulic capacitance and conductivity of the xylem

Drought vulnerability of trees and other woody plants is much debated in the context of climate change, which creates a high interest in understanding plant water relations. The role and functioning of internal water storage is crucial, but still insufficiently understood. Drought vulnerability is typically assessed by considering loss in conductivity in function of decreasing xylem water potential, in a so-called ‘vulnerability curve’. The xylem water potential at which a certain percentage of conductivity is lost (usually 50%) gives an indication of the vulnerability to cavitation. In a ‘desorption curve’, we can examine the release of water from internal storage tissues with decreasing water potential. Both curves are very valuable, but rely on a sequence of manual measurements (xylem water potential, hydraulic conductivity and water content) and are time-consuming. Therefore, we propose a new type of vulnerability curve that is based on continuous measurements of diameter shrinkage and ultrasonic acoustic emissions (UAE). We monitored weight loss, xylem diameter shrinkage and UAE and measured xylem water potential during the dehydration of excised branches of Vitis vinifera L. ‘Johanniter’. The vulnerability curves could be interpreted in terms of water loss in elastic and inelastic tissues. The proposed method can be a tool to assess hydraulic capacitance and conductivity of the xylem

Measuring teat dimensions using image analysis

The interaction between teat and teatcup liner can strongly affect the milking characteristics and udder health. Therefore teat morphology is an important parameter in choosing the most appropriate liner. Nevertheless, teat morphology is rarely considered in choosing a teatcup liner. Gathering information on teat morphology on large scale with current techniques is time consuming, subjective and not always accurate. However, the ability to measure teat shape parameters in an easy way and on large scale has many applications. This study presents a new vision based measuring system that uses a camera to obtain a 2D image of the teat and image processing analyses to determine teat length and diameters. The technique is proven to be accurate (error less than 6%), repeatable and reproducible for both teat length and diameters

Industrial chicory genome gives insights into the molecular timetable of anther development and male sterility

Industrial chicory (Cichorium intybus var. sativum) is a biannual crop mostly cultivated for extraction of inulin, a fructose polymer used as a dietary fiber. F1 hybrid breeding is a promising breeding strategy in chicory but relies on stable male sterile lines to prevent self-pollination. Here, we report the assembly and annotation of a new industrial chicory reference genome. Additionally, we performed RNA-Seq on subsequent stages of flower bud development of a fertile line and two cytoplasmic male sterile (CMS) clones. Comparison of fertile and CMS flower bud transcriptomes combined with morphological microscopic analysis of anthers, provided a molecular understanding of anther development and identified key genes in a range of underlying processes, including tapetum development, sink establishment, pollen wall development and anther dehiscence. We also described the role of phytohormones in the regulation of these processes under normal fertile flower bud development. In parallel, we evaluated which processes are disturbed in CMS clones and could contribute to the male sterile phenotype. Taken together, this study provides a state-of-the-art industrial chicory reference genome, an annotated and curated candidate gene set related to anther development and male sterility as well as a detailed molecular timetable of flower bud development in fertile and CMS lines

Automatic plant-based water status monitoring in grapevine using an improved water transport and storage model

As all plants, grapevines (Vitis vinifera L.) need water to function properly. A certain level of drought stress might however be beneficial as it improves the composition of the grape. Earlier research has shown that differences in water status result in wines with different appearance, aroma, flavour and colour. Nevertheless, the level and timing is of utmost importance. Therefore, an adequate monitoring of the water status is crucial for improving grape (and wine) quality. It is internationally recognised that this should be based on plant measurements, because only then information is gained about the actual plant water status. Mechanistic models are promising for this purpose and allow a deeper understanding of the underlying mechanisms. In this study we use a dynamic water transport and storage model that links sap flow, or whole plant water consumption, and stem diameter variations in order to simulate stem water potential. This variable is considered as one of the best indicators for water status. We aimed at improving the model to perform well under both wet and pronounced dry conditions and evaluated it for real-time water status monitoring. To this end, the former constant flow resistance in the xylem has been replaced by a dynamic resistance depending on measured soil water potential and combines the resistance experienced in the soil, roots and stem. Furthermore, also the radial flow resistance (between xylem and storage tissues), originally implemented as a constant value, has been replaced by an equation. The improved model is able to accurately simulate the plant water status during both wet and pronounced dry conditions. The model seems very promising to apply as an automatic plant-based water status monitoring system and may be a tool to improve grape and wine quality