Nicola Cooley

Ecotypic differences in responses of Arabidopsis thaliana L. to elevated polychromatic UV-A and UV-B+A radiation in the natural environment: a positive correlation between UV-B+A inhibition and growth rate

The effects of supplementary ultraviolet-A (UV-A) and ultraviolet-B+A (UV-B+A) in the natural environment on the growth and morphology of various ecotypes of Arabidopsis thaliana were investigated. The ecotypes investigated were Columbia (Col-4), Landsberg erecta (Ler-0), Cvi-0, Wassilewskija, Enkheim-D, Aa-0 and Di-1. The mutant hy-4 was also used. Results varied with the radiation treatment, ecotype and parameter measured. Plants subjected to elevated UV-A were both insensitive (all parameters Cvi-0 and Col-4) and sensitive. When responses to UV-A occurred they were mostly inhibitory (all significant responses of Di-1 and Enkheim-D, most parameters of Wassilewskija, and some parameters of hy-4), however, promotive affects were observed for some parameters of Aa-0 and Ler-0. Supplementary UV-B+A inhibited all parameters of Di-1 and Enkheim-D and most parameters of Col-4, Ler-0 and hy-4, but Wassilewskija, Aa-0 and Cvi-0 were mostly insensitive. The magnitude of the UV-B+A response varied with ecotype (compare Di-1 with Ler-0). Some ecotypes were sensitive to UV-A but not UV-B+A (Aa-0), whereas others (Ler-0, Col-4) show the opposite sensitivities. A linear relationship is reported between the degree of UV-B+A inhibition of each ecotype and growth rate. The higher the growth rate the more susceptible the ecotype is to UV-B+A inhibition. This relationship holds for the majority of growth parameters measured.

Management practices impact vine carbohydrate status to a greater extent than vine productivity

Light pruning and deficit irrigation regimes are practices which are widely used in high yielding commercial vineyards in the warm climate regions of Australia. Little information is available on their impacts on carbohydrate dynamics in vegetative organs within and between seasons, and on the resulting plant capacity to maintain productivity and ripen fruits. This study was conducted to address this gap in knowledge over five vintages on Vitis vinifera L. cv. Cabernet Franc, Shiraz, and Cabernet Sauvignon in the Sunraysia region of Victoria, Australia. Lighter pruning did not change the total carbohydrates concentration and composition in wood and roots within seasons in Cabernet Franc and Shiraz. However, the total carbohydrate pool (starch and soluble sugars) at the end of dormancy increased under lighter pruning, due to higher vine size, associated with retention and growth of old-wood (trunk and cordons). Water deficit negatively impacted trunk and leaf starch concentrations, over the day and within seasons in Cabernet Sauvignon. Soluble sugars concentrations in these tissues tended to be higher under limited water supply, possibly due to higher sugar mobilization as photosynthesis decreased. Trunk carbohydrate concentrations markedly varied within and between seasons, highlighting the importance of interactive factors such as crop load and climate on carbon status. The period between fruit-set and véraison was shown to be critical for its impact on the balance between carbon accretion and depletion, especially under water deficit. The lower leaf and trunk starch concentration under water deficit resulted in a decrease of yield components at harvest, while similar yields were reached for all pruning systems. The sugar allocated to berries at harvest remained remarkably stable for all practices and seasons, irrespective of vine yield and carbohydrate status in vegetative organs in Shiraz and Cabernet Sauvignon.

Efficient registration of optical and infrared images via modified Sobel edging for plant canopy temperature estimation

Automatic optical and infrared (IR) image registration is a crucial requirement in the estimation of plant canopy temperature. The latter is used to compute the plant water stress status which can potentially be applied to an automated control system for optimal crop irrigation management. Due to the nature of image sources and plant scene, it is difficult to find enough common features between the pair of images to register them using a simple method. In this paper an improved registration algorithm is described, where a modified Sobel edge detector is adopted and a variable resolution scheme is applied. The algorithm can improve the registration efficiency considerably compared to our previous developed registration method. Experiment results show that the modified algorithm can achieve the same registration accuracy and a better success rate compared to that from the original algorithm with a substantial reduction of computational complexity.

A Systems Engineering Approach to Viticulture On-Farm Irrigation

Abstract Water resources management presents an important research topic, because our planet is facing a serious water crisis. About 70% of all fresh water usage goes towards agriculture. Moreover, low water application efficiency are well reported in the literature. Improving on-farm irrigation efficiency can make a substantial contribution to a more sustainable utilization of the worlds fresh water resources. It is argued that systems engineering principles can assist to realize the goal of improving water efficiency or produce quality in on-farm irrigation whilst maintaining productivity and quality of service. In approaching this resource management problem, wireless sensor network technologies and automation ideas are combined to improve economic productivity in dairy, horticulture and viticulture industries in such a way as to support continued growth in these major food industries in the face of a competitive water market. This paper reports the early progress of the project on smart irrigation system for viticulture and initial attempt in modeling the viticulture soil-water dynamics is briefly discussed. The results obtained are encouraging indicating that water automation is a promising technology.

Modeling Dynamic Laser Speckle Patterns of Plant Leaves

t is known that dynamic speckle patterns can be used to identify the temporal evolution of an active sample and some desired properties of the sample may therefore be detected via the dynamic laser speckle analysis. Mathematically understand the structure of sample surface which gives arise to the dynamic speckle patterns is crucial to the analysis. In this paper, a simulation model of the dynamic speckle patterns for plant leaves is proposed. The developed model is derived from the principle of coherent electromagnetic wave scattering off a randomly textured and time varying surface and is demonstrated via the simulation of dynamic speckle patterns of a fresh unattached leaf surface along the true laser speckle measurements. Both simulated and true measurements of the dynamic speckle patterns of the leaf are analyzed via several statistical techniques and a consistent agreement between the results of the two is observed. The proposed statistical model is helpful to gain the insight of the relationship between speckle dynamics and the activity of the leaf surface which is supposed to be an measurement of plant water stress and water status.

Application of laser speckle pattern analysis for plant sensing

Laser speckle interferometry is used to detect micro-structure and its dynamic behavior of a sample surface by the statistical analysis of its laser speckle images. In this paper, the methodology of laser speckling and statistical analysis are studied with the aims to develop a non-contact, non-destructive surface sensing technique which potentially devices a compact, cost-effective tool for measuring the biological status of a plant by scanning its leaves. First, an auto-correlation based analysis method is proposed for the discrimination of various surface roughness levels using their laser speckle statistics. Second, techniques for dynamic speckle pattern analysis for the detection of the evolution of a time-varying sample surface are discussed. The effectiveness of proposed measurement methods are demonstrated via the experiment on a detached leaf.

Automation of on-farm irrigation: Horticultural case study

Abstract Our planet is facing a serious fresh water crisis and improved management of water resources presents significant research challenges. About 70% of the worlds fresh water is consumed by agriculture and water application efficiencies are typically low. Improving the efficiency of water use in agriculture would deliver substantial economic and environmental benefits. To help address the issue of low water application efficiency, wireless sensor network technologies can be combined with automation to support the efficient production of food in a increasingly water limited future. This paper reports on results of combining these approaches to irrigate an apple orchard, where existing irrigation scheduling was predominately based on time consuming manual acquisition of soil moisture data. The system developed allowed fully automated on-farm irrigation based on real-time feedback control which increased economic water use efficiency by 73% compared with manual irrigation. It is suggested that the application of real-time feedback automation would dramatically improve economic efficiency for irrigators with low water efficiency. Whereas, for those irrigators already achieving high water efficiency, adoption of the technology provides substantial labour and time savings.

Automatic Optical and Infrared Image Registration for Plant Water Stress Sensing

In many countries around the world, about 70% of water resource will be used to for agriculture irrigation each year. Precisely control irrigation can significantly reduce the waste of irrigation water while increasing plant productivity. Automated sensing of plant water status via non-destructive, automatic techniques plays a central role in such irrigation control system development. Plant canopy temperature acts as a good indicator of the plant water status. When plants experience water stress, their temperature increases. A novel approach to irrigation scheduling and thus, potential water savings, is to monitor plant temperature and relate to the plants water status. To say further, if we want to know the plant water status, we need to know the canopy temperature at first. Recent research in agriculture indicates that plant water status may be monitored if the canopy temperature distribution of the plant is known (Jones, 1999a,b; Jones and Leinonen, 2003; Guilioni, et al., 2008; Grant, et al., 2007; Wheaton et al., 2007). Plant water status information can be obtained via the computation of the crop water stress index (CWSI) (Jones, 1999a). This index offers great potential to generate an automated irrigation control system where plant canopy temperature distribution is acquired via thermal imaging. Such a system is expected to be able to optimize irrigation water usage and the potential to maintain plant health in real time, thus increasing the productivity of limited water resources. Typically, measurement data of the infrared (IR) thermography sensing system consists of a reference optical image and an IR image. The optical image is obtained by using a normal digital camera and is taken at the same location as the IR image to provide a true view of the IR image scene, one may identify the area of interest (e.g., plant leaves other than ground or sky) from the optical image. The optical image allows the underlying plant canopy of interest to be flawlessly identified. To quantify plant water stress, the value of CWSI is calculated based on the canopy temperature, and temperatures of a dry and wet reference surface. These temperatures can be estimated once the temperature distribution of the