Sigfredo Fuentes

Protocol: optimising hydroponic growth systems for nutritional and physiological analysis of Arabidopsis thaliana and other plants

BackgroundHydroponic growth systems are a convenient platform for studying whole plant physiology. However, we found through trialling systems as they are described in the literature that our experiments were frequently confounded by factors that affected plant growth, including algal contamination and hypoxia. We also found the way in which the plants were grown made them poorly amenable to a number of common physiological assays.ResultsThe drivers for the development of this hydroponic system were: 1) the exclusion of light from the growth solution; 2) to simplify the handling of individual plants, and 3) the growth of the plant to allow easy implementation of multiple assays. These aims were all met by the use of pierced lids of black microcentrifuge tubes. Seed was germinated on a lid filled with an agar-containing germination media immersed in the same solution. Following germination, the liquid growth media was exchanged with the experimental solution, and after 14-21 days seedlings were transferred to larger tanks with aerated solution where they remained until experimentation. We provide details of the protocol including composition of the basal growth solution, and separate solutions with altered calcium, magnesium, potassium or sodium supply whilst maintaining the activity of the majority of other ions. We demonstrate the adaptability of this system for: gas exchange measurement on single leaves and whole plants; qRT-PCR to probe the transcriptional response of roots or shoots to altered nutrient composition in the growth solution (we demonstrate this using high and low calcium supply); producing highly competent mesophyll protoplasts; and, accelerating the screening of Arabidopsis transformants. This system is also ideal for manipulating plants for micropipette techniques such as electrophysiology or SiCSA.ConclusionsWe present an optimised plant hydroponic culture system that can be quickly and cheaply constructed, and produces plants with similar growth kinetics to soil-grown plants, but with the advantage of being a versatile platform for a myriad of physiological and molecular biological measurements on all plant tissues at all developmental stages. We present ‘tips and tricks’ for the easy adoption of this hydroponic culture system.

Partial rootzone drying and deficit irrigation increase stomatal sensitivity to vapour pressure deficit in anisohydric grapevines

The aim of this study was to investigate how alternative irrigation strategies affected grapevine (Vitis vinifera L.) stomatal response to atmospheric vapour pressure deficit (VPD). In two sites, application of partial rootzone drying (PRD) at 90–100% of crop evapotranspiration (ETc) increased stomatal sensitivity of Shiraz (Syrah) grapevines to high VPD compared with control vines irrigated with the same amount of water but applied on both sides of the vine. PRD significantly reduced vine water use (ESF) measured as sap flow and in dry conditions increased the depth of water uptake from the soil profile. In both experiments, PRD reduced vine water use by up to 50% at moderate VPD (~3 kPa) compared with control vines irrigated at the same level. In the same vines, the response to PRD applied at 100% ETc and deficit irrigation applied at 65% ETc was the same, increasing stomatal sensitivity to VPD and decreasing sap flow. Hydraulic signalling apparently did not play a role in changing stomatal sensitivity as there was no difference in stem water potentials between any of the treatment (PRD and DI) and control vines. This suggests that a long distance root-based chemical signal such as ABA may be responsible for the changes in stomatal behaviour. Shiraz grapevines have previously been classified as anisohydric-like, but application of PRD and DI increased stomatal closure in response to conditions of high evaporative demand making the vines behave in a more isohydric-like manner.

An automated procedure for estimating the leaf area index (LAI) of woodland ecosystems using digital imagery, MATLAB programming and its application to an examination of the relationship between remotely sensed and field measurements of LAI

Leaf area index (LAI) is one of the most important variables required for modelling growth and water use of forests. Functional-structural plant models use these models to represent physiological processes in 3-D tree representations. Accuracy of these models depends on accurate estimation of LAI at tree and stand scales for validation purposes. A recent method to estimate LAI from digital images (LAID) uses digital image capture and gap fraction analysis (Macfarlane et al. 2007b) of upward-looking digital photographs to capture canopy LAID (cover photography). After implementing this technique in Australian evergreen Eucalyptus woodland, we have improved the method of image analysis and replaced the time consuming manual technique with an automated procedure using a script written in MATLAB 7.4 (LAIM). Furthermore, we used this method to compare MODIS LAI values with LAID values for a range of woodlands in Australia to obtain LAI at the forest scale. Results showed that the MATLAB script developed was able to successfully automate gap analysis to obtain LAIM. Good relationships were achieved when comparing averaged LAID and LAIM (LAIM = 1.009 - 0.0066 LAID; R2 = 0.90) and at the forest scale, MODIS LAI compared well with LAID (MODIS LAI = 0.9591 LAID - 0.2371; R2 = 0.89). This comparison improved when correcting LAID with the clumping index to obtain effective LAI (MODIS LAI = 1.0296 LAIe + 0.3468; R2 = 0.91). Furthermore, the script developed incorporates a function to connect directly a digital camera, or high resolution webcam, from a laptop to obtain cover photographs and LAI analysis in real time. The later is a novel feature which is not available on commercial LAI analysis softwares for cover photography. This script is available for interested researchers.

An analysis of the sensitivity of sap flux to soil and plant variables assessed for an Australian woodland using a soil–plant–atmosphere model

Daily and seasonal patterns of tree water use were measured for the two dominant tree species, Angophora bakeri E.C.Hall (narrow-leaved apple) and Eucalyptus sclerophylla (Blakely) L.A.S. Johnson & Blaxell (scribbly gum), in a temperate, open, evergreen woodland using sap flow sensors, along with information about soil, leaf, tree and micro-climatological variables. The aims of this work were to: (a) validate a soil-plant-atmosphere (SPA) model for the specific site; (b) determine the total depth from which water uptake must occur to achieve the observed rates of tree sap flow; (c) examine whether the water content of the upper soil profile was a significant determinant of daily rates of sap flow; and (d) examine the sensitivity of sap flow to several biotic factors. It was found that: (a) the SPA model was able to accurately replicate the hourly, daily and seasonal patterns of sap flow; (b) water uptake must have occurred from depths of up to 3 m; (c) sap flow was independent of the water content of the top 80 cm of the soil profile; and (d) sap flow was very sensitive to the leaf area of the stand, whole tree hydraulic conductance and the critical water potential of the leaves, but insensitive to stem capacitance and increases in root biomass. These results are important to future studies of the regulation of vegetation water use, landscape-scale behaviour of vegetation, and to water resource managers, because they allow testing of large-scale management options without the need for large-scale manipulations of vegetation cover.

Computational water stress indices obtained from thermal image analysis of grapevine canopies

Thermal imaging of crop canopies has been proposed more than a decade ago as a sensitive methodology to determine the water status of different crops. This paper describes the development of a semi-automated and automated methodology using MATLAB® programming techniques to analyse the infrared thermal images taking into consideration the pitfalls pointed out previously in the literature. The proposed method was tested in an irrigation reduction and recovery trial for Chardonnay in the 2010–2011 season and in the 2009–2010 season from seven varieties in field conditions. There was a clear separation (assessed by principal component analysis) between control and recovery compared to stress treatments using leaf area index (LAI), stomatal conductance, stem water potential and indices derived from canopy temperatures measured by infrared imaging. High and significant correlations were found between canopy temperature indices and other measures of water stress obtained in the same vines that were independent of LAI. Furthermore, a fully automated analysis method has been proposed using ancillary weather information obtained from the same locations of infrared thermal images. This paper is a first step towards automation of infrared thermography acquisition and analysis in the field for grapevines and other crops.

Within-Vineyard, Within-Vine, and Within-Bunch Variability of the Rotundone Concentration in Berries of Vitis vinifera L. cv. Shiraz

This study characterizes the environmental factors driving rotundone concentrations in grape berries by quantifying rotundone variability and correlating it with viticultural parameters. Dissection of the vineyard into distinct zones (on the basis of vigor, electrical soil conductivity, and slope), vine into orientations to sun (shaded/unshaded), and grape bunches into sectors (upper and lower and front and back) shows the influence of vine vigor, sunlight, and temperature. Occurrence of the highest rotundone concentration was observed in shaded bunch sectors and vines and from higher vigor vines in the southern-facing areas of the vineyard. The highest concentration of rotundone is consistently found at the top and in shaded sectors of bunches, and this correlates to lower grape surface temperatures. Modeling showed that berry temperature exceeding 25 °C negatively affects the rotundone concentration in Shiraz. Both natural and artificial shading modulated the grape surface and air temperature at the bunch zone and increased the rotundone concentration, without affecting other grape berry quality parameters. Thus, temperature and possibly sunlight interception are the main determinants of rotundone in grape berries. Vineyard topography, vine vigor, vine row, and grape bunch orientation influence the level of berry shading and can, therefore, adjust bunch surface and zone temperatures and influence the berry rotundone concentration.

Environmental Factors and Seasonality Affect the Concentration of Rotundone in Vitis vinifera L. cv. Shiraz Wine

Rotundone is a sesquiterpene that gives grapes and wine a desirable ‘peppery’ aroma. Previous research has reported that growing grapevines in a cool climate is an important factor that drives rotundone accumulation in grape berries and wine. This study used historical data sets to investigate which weather parameters are mostly influencing rotundone concentration in grape berries and wine. For this purpose, wines produced from 15 vintages from the same Shiraz vineyard (The Old Block, Mount Langi Ghiran, Victoria, Australia) were analysed for rotundone concentration and compared to comprehensive weather data and minimal temperature information. Degree hours were obtained by interpolating available temperature information from the vineyard site using a simple piecewise cubic hermite interpolating polynomial method (PCHIP). Results showed that the highest concentrations of rotundone were consistently found in wines from cool and wet seasons. The Principal Component Analysis (PCA) showed that the concentration of rotundone in wine was negatively correlated with daily solar exposure and grape bunch zone temperature, and positively correlated with vineyard water balance. Finally, models were constructed based on the Gompertz function to describe the dynamics of rotundone concentration in berries through the ripening process according to phenological and thermal times. This characterisation is an important step forward to potentially predict the final quality of the resultant wines based on the evolution of specific compounds in berries according to critical environmental and micrometeorological variables. The modelling techniques described in this paper were able to describe the behaviour of rotundone concentration based on seasonal weather conditions and grapevine phenological stages, and could be potentially used to predict the final rotundone concentration early in future growing seasons. This could enable the adoption of precision irrigation and canopy management strategies to effectively mitigate adverse impacts related to climate change and microclimatic variability, such as heat waves, within a vineyard on wine quality.

Automated computation of leaf area index from fruit trees using improved image processing algorithms applied to canopy cover digital photograpies

Proposed improvement of leaf area index estimation for fruit trees using a two-level automated segmentation to isolate non-leaf material from the analysis where: (a) is the original image; (b), (c) and (d) are the resulting images for the first segmentation level and (e), (f) and (g) are the resulting images for the second segmentation level.Display Omitted An improved image analysis method to estimate leaf area index has been tested.Improvements consist in image segmentation algorithms to exclude non-leaf material.Results suggest that this method is an affordable alternative to compute LAI. Leaf area index (LAI) is a critical parameter in plant physiology for models related to growth, photosynthetic activity and evapotranspiration. It is also important for farm management purposes, since it can be used to assess the vigor of trees within a season with implications in water and fertilizer management. Among the diverse methodologies to estimate LAI, those based on cover photography are of great interest, since they are non-destructive, easy to implement, cost effective and have been demonstrated to be accurate for a range of tree species. However, these methods could have an important source of error in the LAI estimation due to the inclusion within the analysis of non-leaf material, such as trunks, shoots and fruits depending on the complexity of canopy architectures. This paper proposes a modified cover photography method based on specific image segmentation algorithms to exclude contributions from non-leaf materials in the analysis. Results from the implementation of this new image analysis method for cherry tree canopies showed a significant improvement in the estimation of LAI compared to ground truth data using allometric methods and previously available cover photography methods. The proposed methodological improvement is very simple to implement, with numerical relevance in species with complex 3D canopies where the woody elements greatly influence the total leaf area.

VitiCanopy: A Free Computer App to Estimate Canopy Vigor and Porosity for Grapevine

Leaf area index (LAI) and plant area index (PAI) are common and important biophysical parameters used to estimate agronomical variables such as canopy growth, light interception and water requirements of plants and trees. LAI can be either measured directly using destructive methods or indirectly using dedicated and expensive instrumentation, both of which require a high level of know-how to operate equipment, handle data and interpret results. Recently, a novel smartphone and tablet PC application, VitiCanopy, has been developed by a group of researchers from the University of Adelaide and the University of Melbourne, to estimate grapevine canopy size (LAI and PAI), canopy porosity, canopy cover and clumping index. VitiCanopy uses the front in-built camera and GPS capabilities of smartphones and tablet PCs to automatically implement image analysis algorithms on upward-looking digital images of canopies and calculates relevant canopy architecture parameters. Results from the use of VitiCanopy on grapevines correlated well with traditional methods to measure/estimate LAI and PAI. Like other indirect methods, VitiCanopy does not distinguish between leaf and non-leaf material but it was demonstrated that the non-leaf material could be extracted from the results, if needed, to increase accuracy. VitiCanopy is an accurate, user-friendly and free alternative to current techniques used by scientists and viticultural practitioners to assess the dynamics of LAI, PAI and canopy architecture in vineyards, and has the potential to be adapted for use on other plants.

Digital Cover Photography for Estimating Leaf Area Index (LAI) in Apple Trees Using a Variable Light Extinction Coefficient

Leaf area index (LAI) is one of the key biophysical variables required for crop modeling. Direct LAI measurements are time consuming and difficult to obtain for experimental and commercial fruit orchards. Devices used to estimate LAI have shown considerable errors when compared to ground-truth or destructive measurements, requiring tedious site-specific calibrations. The objective of this study was to test the performance of a modified digital cover photography method to estimate LAI in apple trees using conventional digital photography and instantaneous measurements of incident radiation (Io) and transmitted radiation (I) through the canopy. Leaf area of 40 single apple trees were measured destructively to obtain real leaf area index (LAID), which was compared with LAI estimated by the proposed digital photography method (LAIM). Results showed that the LAIM was able to estimate LAID with an error of 25% using a constant light extinction coefficient (k = 0.68). However, when k was estimated using an exponential function based on the fraction of foliage cover (ff) derived from images, the error was reduced to 18%. Furthermore, when measurements of light intercepted by the canopy (Ic) were used as a proxy value for k, the method presented an error of only 9%. These results have shown that by using a proxy k value, estimated by Ic, helped to increase accuracy of LAI estimates using digital cover images for apple trees with different canopy sizes and under field conditions.