Effect of stripe rust on the yield response of wheat to nitrogen

Nitrogen(N) is the most important fertiliser element determining the productivity of wheat.N nutrition is known to affect the level of stripe rust infection, with higher N associated with increased disease severity. Stripe rust, caused by Puccinia striiformis f. sp. tritici, is a major yield-limiting disease of wheat in Australia. This paper describes experiments designed to investigate the agronomic response to the interaction of various levels of N application and stripe rust severity in wheat varieties differing in response. Experimental plots were established in crop seasons 2006 and 2007 on the Liverpool Plains of northern NSW, Australia.Yield, biomass, grain protein content(GPC) and harvest index(HI) data were recorded.Increased rates of N increased the severity of stripe rust during grain filling. N application also increased yield and GPC in all varieties in both years. Stripe rust reduced the yield of the rust-susceptible wheat varieties, and GPC and proportion of added N recovered in the grain were also reduced in one year but not the other. It was evident from our experiment that stripe rust caused yield loss accompanied by either no change or reduction in GPC, indicating that the total amount of N entering the grain was reduced by stripe rust. The effects of stripe rust on N yield are most likely associated with reduced uptake of N during grain filling.

A Model for RF Loss through Vegetation with Varying Water Content

Assessing plant water status is important for monitoring plant physiology. Radio signals are attenuated when passing through vegetation. Both analytical and empirical models developed for radio frequency (RF) loss through vegetation have been dependent on experimental measurements and those measurements have been completed in specific situations. However, for models to be more broadly applicable across a broad range of vegetation types and constructs, basic electrical properties of the vegetation need to be characterised. Radio waves are affected especially by water and the relationship between water content in vegetation expressed as effective water path (EWP) in mm and measured RF loss (dB) at 2.4 GHz was investigated in this work. The EWP of eucalyptus leaves of varying amounts of leaf moisture (0% - 41.5%) ranged from 0 - 14 mm, respectively. When the model was compared with the actual RF loss there was a systematic offset equivalent to a residual leaf moisture content of 6.5% that was unaccounted for in the leaf moisture content determination (oven drying). This was attributed to bound water. When the model was adjusted for this amount of additional leaf water, the average RMSE in predicted RF loss was ±2.2 dB and was found to explain 89% of the variance in measured RF loss.

A Novel Approach for Sugarcane Yield Prediction Using Landsat Time Series Imagery: A Case Study on Bundaberg Region

Quantifying sugarcane production is critical for a wide range of applications, including crop management and decision making processes such as harvesting, storage, and forward selling. This study explored a novel model for predicting sugarcane yield in Bundaberg region from time series Landsat data. From the freely available Landsat archive, 98 cloud free (<40%) Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper (ETM+) images, acquired between November 15th to July 31st (2001-2015) were sourced for this study. The images were masked using the field boundary layer vector files of each year and the GNDVI was calculated. An analysis of average green normalized difference vegetation index (GNDVI) values from all sugarcane crops grown within the Bundaberg region over the 15 year period identified the beginning of April as the peak growth stage and, therefore, the optimum time for satellite image based yield forecasting. As the GNDVI is an indicator of crop vigor, the model derived maximum GNDVI was regressed against historical sugarcane yield data, which showed a significant correlation with R2 = 0.69 and RMSE = 4.2 t/ha. Results showed that the model derived maximum GNDVI from Landsat imagery would be a feasible and a modest technique to predict sugarcane yield in Bundaberg region.

Prediction of Water Content of Eucalyptus Leaves Using 2.4 GHz Radio Wave

Assessing plant water status is important for monitoring plant physiology. Previous studies showed that radio waves are attenuated when passing through vegetation such as trees. The degree of radio frequency (RF) loss has previously been measured for various tree types but the relationship between water content and RF loss has not been quantified. In this study, the amount of water inside leaves was expressed as an effective water path (EWP), the thickness of a hypothetical sheet of 100% water with the same mass. A 2.4331 GHz radio wave was transmitted through a wooden frame covered on both sides with 5 mm clear acrylic sheets and filled with Eucalyptus laevopinea leaves. The RF loss through the leaves was measured for different stages of drying. The results showed that there is a nonlinear relationship between effective water path (EWP) in mm and RF loss in dB. It can be concluded that 2.4 GHz frequency radio waves can be used to predict the water content inside eucalyptus leaves (0 < EWP < 14 mm;RMSE ± 0.87 mm) and demonstrates the potential to measure the water content of whole trees.

RF Loss Model for Tree Canopies with Varying Water Content

Detection of plant water status is important for monitoring plant physiology. Previous studies showed that radio waves are attenuated when passing through vegetation such as trees, and models (both empirical and analytical) were developed. However, for models to be more broadly applicable across a broad range of vegetation types and constructs, basic electrical properties of the vegetation need to be characterised. In our previous work, a model was developed to calculate the RF loss through vegetation with varying water content. In this paper, the model was extended to calculate RF loss through tree canopies with or without an air gap. When the model was compared with the actual RF loss acquired using Eucalyptus blakelyi trees (with and without leaves), there was a systematic offset equivalent to a residual moisture content of 13% that was attributed to bound water. When the model was adjusted for the additional water content, the effective water path (EWP) was found to explain 72% of the variance in the measured RF loss.