Remote sensing of nitrogen and water stress in wheat

Nitrogen (N) is the largest agricultural input in many Australian cropping systems and applying the right amount of N in the right place at the right physiological stage is a significant challenge for wheat growers. Optimizing N uptake could reduce input costs and minimize potential off-site movement. Since N uptake is dependent on soil and plant water status, ideally, N should be applied only to areas within paddocks with sufficient plant available water. To quantify N and water stress, spectral and thermal crop stress detection methods were explored using hyperspectral, multispectral and thermal remote sensing data collected at a research field site in Victoria, Australia. Wheat was grown over two seasons with two levels of water inputs (rainfall/irrigation) and either four levels (in 2004; 0, 17, 39 and 163 kg/ha) or two levels (in 2005; 0 and 39 kg/ha N) of nitrogen. The Canopy Chlorophyll Content Index (CCCI) and modified Spectral Ratio planar index (mSRpi), two indices designed to measure canopy-level N, were calculated from canopy-level hyperspectral data in 2005. They accounted for 76% and 74% of the variability of crop N status, respectively, just prior to stem elongation (Zadoks 24). The Normalised Difference Red Edge (NDRE) index and CCCI, calculated from airborne multispectral imagery, accounted for 41% and 37% of variability in crop N status, respectively. Greater scatter in the airborne data was attributable to the difference in scale of the ground and aerial measurements (i.e., small area plant samples against whole-plot means from imagery). Nevertheless, the analysis demonstrated that canopy-level theory can be transferred to airborne data, which could ultimately be of more use to growers. Thermal imagery showed that mean plot temperatures of rainfed treatments were 2.7 °C warmer than irrigated treatments (P < 0.001) at full cover. For partially vegetated fields, the two-Dimensional Crop Water Stress Index (2D CWSI) was calculated using the Vegetation Index-Temperature (VIT) trapezoid method to reduce the contribution of soil background to image temperature. Results showed rainfed plots were consistently more stressed than irrigated plots. Future work is needed to improve the ability of the CCCI and VIT methods to detect N and water stress and apply both indices simultaneously at the paddock scale to test whether N can be targeted based on water status. Use of these technologies has significant potential for maximising the spatial and temporal efficiency of N applications for wheat growers. ‘Ground–breaking Stuff’- Proceedings of the 13th Australian Society of Agronomy Conference, 10-14 September 2006, Perth, Western Australia.

Evaluation of a remote drafting system for regulating sheep access to supplement

Remote drafting technology now available for sheep makes possible targeted supplementation of individuals within a grazing flock. This system was evaluated by using 68 Merino wethers grazing dry-season, native Mitchell grass pasture (predominantly Astrebla spp.) as a group and receiving access to lupin grain through a remote drafter 0, 1, 2, 4 or 7 days/week for 8 weeks. The sole paddock watering point was separately fenced and access was via a one-way flow gate. Sheep exited the watering point through a remote drafter operated by solar power and were drafted by radio frequency identification (RFID) tag, according to treatment, either back into the paddock or into a common supplement yard where lupins were provided ad libitum in a self-feeder. Sheep were drafted into the supplement yard on only their first time through the drafter during the prescribed 24-h period and exited the supplement yard via one-way flow gates in their own time. The remote drafter operated with a high accuracy, with only 2.1% incorrect drafts recorded during the experimental period out of a total of 7027 sheep passes through the remote drafter. The actual number of accesses to supplement for each treatment group, in order, were generally less than that intended, i.e. 0.02, 0.69, 1.98, 3.35 and 6.04 days/week. Deviations from the intended number of accesses to supplement were mainly due to sheep not coming through to water on their allocated day of treatment access, although some instances were due to incorrect drafts. There was a non-linear response in growth rate to increased frequency of access to lupins with the growth rate response plateauing at similar to 3 actual accesses per week, corresponding to a growth rate of 72.5 g/head. day. This experiment has demonstrated the application of the remote drafting supplementation system for the first time under grazing conditions and with the drafter operated completely from solar power. The experiment demonstrates a growth response to increasing frequency of access to supplement and provides a starting point with which to begin to develop feeding strategies to achieve sheep weight-change targets.

Remote sensing applications for cotton.

This paper compares classified normalized difference vegetation index images of cotton crops derived from both low and high resolution satellite imagery to determine the most accurate and feasible option for Australian cotton growers. It also demonstrates a rapid automated processing and internet delivery system for distributing satellite SPOT-2 imagery. Also provided is the profile of two case studies conducted in the Darling Towns demonstrating the potential benefit of adopting this technology for improving in-season agronomic crop assessments and therefore enable improved management decisions to be made.

Remote Sensing - based precision agriculture tool for the sugar industry

The project will produce practical and relevant benchmarks, protocols and recommendations for the adoption of remote sensing technologies for improved in season management and therefore production within the Australian sugar cane industry.

Remote sensing to implement an effective pest management strategy for canegrubs

Develop a remote-sensing system that can identify canegrub infestations and provide early- warning to growers via the internet.

Precision Agriculture and Remote Sensing Technologies in Central Queensland agricultural production systems

Demonstrate potential benefits of various Precision Agricultural technologies to Central Queensland farming community.

Remote management technologies: Producer demonstration sites Roma region

Technology demonstration sites for remote water management for Roma region.

Separating grazing and rainfall effects at regional scale using remote sensing imagery: A dynamic reference-cover method

Remote detection of management-related trend in the presence of inter-annual climatic variability in the rangelands is difficult. Minimally disturbed reference areas provide a useful guide, but suitable benchmarks are usually difficult to identify. We describe a method that uses a unique conceptual framework to identify reference areas from multitemporal sequences of ground cover derived from Landsat TM and ETM+ imagery. The method does not require ground-based reference sites nor GIS layers about management. We calculate a minimum ground cover image across all years to identify locations of most persistent ground cover in years of lowest rainfall. We then use a moving window approach to calculate the difference between the window's central pixel and its surrounding reference pixels. This difference estimates ground-cover change between successive below-average rainfall years, which provides a seasonally interpreted measure of management effects. We examine the approach's sensitivity to window size and to cover-index percentiles used to define persistence. The method successfully detected management-related change in ground cover in Queensland tropical savanna woodlands in two case studies: (1) a grazing trial where heavy stocking resulted in substantial decline in ground cover in small paddocks, and (2) commercial paddocks where wet-season spelling (destocking) resulted in increased ground cover. At a larger scale, there was broad agreement between our analysis of ground-cover change and ground-based land condition change for commercial beef properties with different a priori ratings of initial condition, but there was also some disagreement where changing condition reflected pasture composition rather than ground cover. We conclude that the method is suitably robust to analyse grazing effects on ground cover across the 1.3 x 10(6) km(2) of Queensland's rangelands. Crown Copyright (c) 2012 Published by Elsevier Inc. All rights reserved.

Refining low-volume, high-concentration herbicide applications to control Chromolaena odorata (L.) King & Robinson (Siam weed) in remote areas

Chromolaena odorata (L.) King and Robinson (Siam weed) is a highly invasive plant and a high priority for control in north Queensland. It can be effectively treated using high-volume, groundbased herbicide spray equipment, but operational information shows that this control method becomes increasingly difficult in areas where vehicle access is prevented by rougher terrain. Low-volume, high-concentration herbicide applications have proven capable of causing high mortality in these remote situations. Two trials were undertaken between May 2010 and May 2012 to refine effective rates of aminopyralid/fluroxypyr, fluroxypyr and metsulfuron-methyl, only using low-volume, high-concentration applications on Siam weed. Fluroxypyr on its own was as effective as aminopyralid/fluroxypyr as both herbicides caused 95-100% mortality at overlapping rates containing 5 to 18.85 g a.i. L-1 of fluroxypyr. Metsulfuron-methyl caused 100% mortality when applied at 3 and 6 g a.i. L-1. Effective control was achieved with approximately 16 to 22 mL of the solutions per plant, so a 5 L mixture in a backpack could treat 170 to 310 adult plants. There are several options for treating Siam weed on the ground and the choice of methods reflects the area, plant density and accessibility of the infestation. Control information from Siam weed field crews shows that low volume, high concentration herbicide applications applied using a splatter gun are a more efficient method for controlling larger, denser remote infestations than physical removal. By identifying effective herbicides that are applied through low-volume equipment, these trials provide an additional and more efficient tool for controlling Siam weed in remote areas.

New developments in UAV remote sensing for pest management and the implications for cotton

Efficient crop monitoring and pest damage assessments are key to protecting the Australian agricultural industry and ensuring its leading position internationally. An important element in pest detection is gathering reliable crop data frequently and integrating analysis tools for decision making. Unmanned aerial systems are emerging as a cost-effective solution to a number of precision agriculture challenges. An important advantage of this technology is it provides a non-invasive aerial sensor platform to accurately monitor broad acre crops. In this presentation, we will give an overview on how unmanned aerial systems and machine learning can be combined to address crop protection challenges. A recent 2015 study on insect damage in sorghum will illustrate the effectiveness of this methodology. A UAV platform equipped with a high-resolution camera was deployed to autonomously perform a flight pattern over the target area. We describe the image processing pipeline implemented to create a georeferenced orthoimage and visualize the spatial distribution of the damage. An image analysis tool has been developed to minimize human input requirements. The computer program is based on a machine learning algorithm that automatically creates a meaningful partition of the image into clusters. Results show the algorithm delivers decision boundaries that accurately classify the field into crop health levels. The methodology presented in this paper represents a venue for further research towards automated crop protection assessments in the cotton industry, with applications in detecting, quantifying and monitoring the presence of mealybugs, mites and aphid pests.