3D modelling of mango fruit skin blush in the tree canopy

The fruit of certain mango cultivars (e.g., 'Honey Gold') can develop blush on their skin. Skin blush due to red pigmentation is from the accumulation of anthocyanins. Anthocyanin biosynthesis is related to environmental determinants, including light received by the fruit. It has been observed that mango skin blush varies with position in the tree canopy. However, little investigation into this spatial relationship has been conducted. The objective of this preliminary study was to describe a 'Honey Gold' mango tree by capturing its three-dimensional (3D) architecture. A light path tracing model QuasiMC was then used to predict light received by fruit. The use of this 3D model was to better understand the relationship between mango fruit skin blush and fruit position in the canopy. The digitised mango tree mimicked the real tree at a high level of detail. Observations on mango skin blush distribution supported the proposition that sunlight exposure is an absolute requirement for anthocyanin development. No blush development occurred on shaded skin. It was affirmed that 3D mapping could allow for virtual experiments. For example, for virtual canopy thinning (e.g., 'window pruning') to admit more sunlight with a view to improve fruit blush. Improvements to 3D modelling of mango skin blush could focus on increasing accuracy, e.g., measurement of leaf light reflectance and transmission and the inclusion of the effect shading by branches.

Measurement of genetic and environmental variation in barley (Hordeum vulgare) grain hardness

In this study, we assessed a broad range of barley breeding lines and commercial varieties by three hardness methods (two particle size methods and one crush resistance method (SKCS—Single-Kernel Characterization System), grown at multiple sites to see if there was variation in barley hardness and if that variation was genetic or environmentally controlled. We also developed near-infrared reflectance (NIR) calibrations for these three hardness methods to ascertain if NIR technology was suitable for rapid screening of breeding lines or specific populations. In addition, we used this data to identify genetic regions that may be associated with hardness. There were significant (p<0.05) genetic effects for the three hardness methods. There were also environmental effects, possibly linked to the effect of protein on hardness, i.e. increasing protein resulted in harder grain. Heritability values were calculated at >85% for all methods. The NIR calibrations, with R2 values of >90%, had Standard Error of Prediction values of 0.90, 72 and 4.0, respectively, for the three hardness methods. These equations were used to predict hardness values of a mapping population which resulted in genetic markers being identified on all chromosomes but chromosomes 2H, 3H, 5H, 6H and 7H had markers with significant LOD scores. The two regions on 5H were on the distal end of both the long and short arms. The region that showed significant LOD score was on the long arm. However, the region on the short arm associated with the hardness (hordoindoline) genes did not have significant LOD scores. The results indicate that barley hardness is influenced by both genotype and environment and that the trait is heritable, which would allow breeders to develop very hard or soft varieties if required. In addition, NIR was shown to be a reliable tool for screening for hardness. While the data set used in this study has a relatively low variation in hardness, the tools developed could be applied to breeding populations that have large variation in barley grain hardness.

Process studies of odour emissions from effluent ponds using machine-based odour measurement

Replicable experimental studies using a novel experimental facility and a machine-based odour quantification technique were conducted to demonstrate the relationship between odour emission rates and pond loading rates. The odour quantification technique consisted of an electronic nose, AromaScan A32S, and an artificial neural network. Odour concentrations determined by olfactometry were used along with the AromaScan responses to train the artificial neural network. The trained network was able to predict the odour emission rates for the test data with a correlation coefficient of 0.98. Time averaged odour emission rates predicted by the machine-based odour quantification technique, were strongly correlated with volatile solids loading rate, demonstrating the increased magnitude of emissions from a heavily loaded effluent pond. However, it was not possible to obtain the same relationship between volatile solids loading rates and odour emission rates from the individual data. It is concluded that taking a limited number of odour samples over a short period is unlikely to provide a representative rate of odour emissions from an effluent pond. A continuous odour monitoring instrument will be required for that more demanding task.

Estimation of light interception in research environments: A joint approach using directional light sensors and 3D virtual plants applied to sunflower (Helianthus annuus) and Arabidopsis thaliana in natural and artificial conditions

Light interception is a major factor influencing plant development and biomass production. Several methods have been proposed to determine this variable, but its calculation remains difficult in artificial environments with heterogeneous light. We propose a method that uses 3D virtual plant modelling and directional light characterisation to estimate light interception in highly heterogeneous light environments such as growth chambers and glasshouses. Intercepted light was estimated by coupling an architectural model and a light model for different genotypes of the rosette species Arabidopsis thaliana (L.) Heynh and a sunflower crop. The model was applied to plants of contrasting architectures, cultivated in isolation or in canopy, in natural or artificial environments, and under contrasting light conditions. The model gave satisfactory results when compared with observed data and enabled calculation of light interception in situations where direct measurements or classical methods were inefficient, such as young crops, isolated plants or artificial conditions. Furthermore, the model revealed that A. thaliana increased its light interception efficiency when shaded. To conclude, the method can be used to calculate intercepted light at organ, plant and plot levels, in natural and artificial environments, and should be useful in the investigation of genotype-environment interactions for plant architecture and light interception efficiency. This paper originates from a presentation at the 5th International Workshop on Functional–Structural Plant Models, Napier, New Zealand, November 2007.

Measurement and Interpretation of Salinity Tolerance in Four Perennial Grasses

Whilst the topic of soil salinity has received a substantive research effort over the years, the accurate measurement and interpretation of salinity tolerance data remain problematic. The tolerance of four perennial grass species (non-halophytes) to sodium chloride (NaCl) dominated salinity was determined in a free-flowing sand culture system. Although the salinity tolerance of non-halophytes is often represented by the threshold salinity model (bent-stick model), none of the species in the current study displayed any observable salinity threshold. Further, the observed yield decrease was not linear as suggested by the model. On re-examination of earlier datasets, we conclude that the threshold salinity model does not adequately describe the physiological processes limiting growth of non-halophytes in saline soils. Therefore, the use of the threshold salinity model is not recommended for non-halophytes, but rather, a model which more accurately reflects the physiological response observed in these saline soils, such as an exponential regression curve.

Developing Queensland 3D Tropical Fruits and Nuts modelling capabilities

Development of 3D functional structural plant models for macadamias and other tropical fruit and nuts.

Hanging drop: An in vitro air toxic exposure model using human lung cells in 2D and 3D structures

Using benzene as a candidate air toxicant and A549 cells as an in vitro cell model, we have developed and validated a hanging drop (HD) air exposure system that mimics an air liquid interface exposure to the lung for periods of 1 h to over 20 days. Dose response curves were highly reproducible for 2D cultures but more variable for 3D cultures. By comparing the HD exposure method with other classically used air exposure systems, we found that the HD exposure method is more sensitive, more reliable and cheaper to run than medium diffusion methods and the CULTEX (R) system. The concentration causing 50% of reduction of cell viability (EC50) for benzene, toluene, p-xylene, m-xylene and o-xylene to A549 cells for 1 h exposure in the HD system were similar to previous in vitro static air exposure. Not only cell viability could be assessed but also sub lethal biological endpoints such as DNA damage and interleukin expressions. An advantage of the HD exposure system is that bioavailability and cell concentrations can be derived from published physicochemical properties using a four compartment mass balance model. The modelled cellular effect concentrations EC50(cell) for 1 h exposure were very similar for benzene, toluene and three xylenes and ranged from 5 to 15 mmol/kg(dry weight) which corresponds to the intracellular concentration of narcotic chemicals in many aquatic species, confirming the high sensitivity of this exposure method. (C) 2013 Elsevier B.V. All rights reserved.

Field measurement of beef pen manure methane and nitrous oxide reveals a surprise for inventory calculations

Few data exist on direct greenhouse gas emissions from pen manure at beef feedlots. However, emission inventories attempt to account for these emissions. This study used a large chamber to isolate N2O and CH4 emissions from pen manure at two Australian commercial beef feedlots (stocking densities, 13-27 m(2) head) and related these emissions to a range of potential emission control factors, including masses and concentrations of volatile solids, NO3-, total N, NH4+, and organic C (OC), and additional factors such as total manure mass, cattle numbers, manure pack depth and density, temperature, and moisture content. Mean measured pen N2O emissions were 0.428 kg ha(-1) d(-1) (95% confidence interval [CI], 0.252-0.691) and 0.00405 kg ha(-1) d(-1) (95% CI, 0.00114-0.0110) for the northern and southern feedlots, respectively. Mean measured CH4 emission was 0.236 kg ha(-1) d(-1) (95% CI, 0.163-0.332) for the northern feedlot and 3.93 kg ha(-1) d(-1) (95% CI, 2.58-5.81) for the southern feedlot. Nitrous oxide emission increased with density, pH, temperature, and manure mass, whereas negative relationships were evident with moisture and OC. Strong relationships were not evident between N2O emission and masses or concentrations of NO3- or total N in the manure. This is significant because many standard inventory calculation protocols predict N2O emissions using the mass of N excreted by the animal.