Sources and seasonal dynamics of Alternaria inoculum associated with leaf blotch and fruit spot of apples

Alternaria leaf blotch and fruit spot caused by Alternaria spp. cause annual losses to the Australian apple industry. Control options are limited, mainly due to a lack of understanding of the disease cycle. Therefore, this study aimed to determine potential sources of Alternaria spp. inoculum in the orchard and examine their relative contribution throughout the production season. Leaf residue from the orchard floor, canopy leaves, twigs and buds were collected monthly from three apple orchards for two years and examined for the number of spores on their surface. In addition, the effects of climatic factors on spore production dynamics in each plant part were examined. Although all four plant parts tested contributed to the Alternaria inoculum in the orchard, significant higher numbers of spores were obtained from leaf residue than the other plant parts supporting the hypothesis that overwintering of Alternaria spp. occurred mainly in leaf residue and minimally on twigs and buds. The most significant period of spore production on leaf residue occurred from dormancy until bloom and on canopy leaves and twigs during the fruit growth stage. Temperature was the single most significant factor influencing the amount of Alternaria inoculum and rainfall and relative humidity showed strong associations with temperature influencing the spore production dynamics in Australian orchards. The practical implications of this study include the eradication of leaf residue from the orchard floor and sanitation of the canopy after harvest to remove residual spores from the trees.

Temporal and spatial patterns of soil water extraction and drought resistance among genotypes of a perennial C-4 grass

The objective of this study was to investigate patterns of soil water extraction and drought resistance among genotypes of bermudagrass (Cynodon spp.) a perennial C-4 grass. Four wild Australian ecotypes (1-1, 25a1, 40-1, and 81-1) and four cultivars (CT2, Grand Prix, Legend, and Wintergreen) were examined in field experiments with rainfall excluded to monitor soil water extraction at 30-190 cm depths. In the study we defined drought resistance as the ability to maintain green canopy cover under drought. The most drought resistant genotypes (40-1 and 25a1) maintained more green cover (55-85% vs 5-10%) during water deficit and extracted more soil water (120-160 mm vs 77-107 mm) than drought sensitive genotypes, especially at depths from 50 to 110 cm, though all genotypes extracted water to 190 cm. The maintenance of green cover and higher soil water extraction were associated with higher stomatal conductance, photosynthetic rate and relative water content. For all genotypes, the pattern of water use as a percentage of total water use was similar across depth and time We propose the observed genetic variation was related to different root characteristics (root length density, hydraulic conductivity, root activity) although shoot sensitivity to drying soil cannot be ruled out.

Plot size matters: interference from intergenotypic competition in plant phenotyping studies

Genetic and physiological studies often comprise genotypes diverse in vigour, size and flowering time. This can make the phenotyping of complex traits challenging, particularly those associated with canopy development, biomass and yield, as the environment of one genotype can be influenced by a neighbouring genotype. Limited seed and space may encourage field assessment in single, spaced rows or in small, unbordered plots, whereas the convenience of a controlled environment or greenhouse makes pot studies tempting. However, the relevance of such growing conditions to commercial field-grown crops is unclear and often doubtful. Competition for water, light and nutrients necessary for canopy growth will be variable where immediate neighbours are genetically different, particularly under stress conditions, where competition for resources and influence on productivity is greatest. Small hills and rod-rows maximise the potential for intergenotypic competition that is not relevant to a crop’s performance in monocultures. Response to resource availability will typically vary among diverse genotypes to alter genotype ranking and reduce heritability for all growth-related traits, with the possible exception of harvest index. Validation of pot experiments to performance in canopies in the field is essential, whereas the planting of multirow plots and the simple exclusion of plot borders at harvest will increase experimental precision and confidence in genotype performance in target environments.

Modelling the effect of plant water use traits on yield and stay-green expression in sorghum

Post-rainy sorghum (Sorghum bicolor (L.) Moench) production underpins the livelihood of millions in the semiarid tropics, where the crop is affected by drought. Drought scenarios have been classified and quantified using crop simulation. In this report, variation in traits that hypothetically contribute to drought adaptation (plant growth dynamics, canopy and root water conducting capacity, drought stress responses) were virtually introgressed into the most common post-rainy sorghum genotype, and the influence of these traits on plant growth, development, and grain and stover yield were simulated across different scenarios. Limited transpiration rates under high vapour pressure deficit had the highest positive effect on production, especially combined with enhanced water extraction capacity at the root level. Variability in leaf development (smaller canopy size, later plant vigour or increased leaf appearance rate) also increased grain yield under severe drought, although it caused a stover yield trade-off under milder stress. Although the leaf development response to soil drying varied, this trait had only a modest benefit on crop production across all stress scenarios. Closer dissection of the model outputs showed that under water limitation, grain yield was largely determined by the amount of water availability after anthesis, and this relationship became closer with stress severity. All traits investigated increased water availability after anthesis and caused a delay in leaf senescence and led to a ‘stay-green’ phenotype. In conclusion, we showed that breeding success remained highly probabilistic; maximum resilience and economic benefits depended on drought frequency. Maximum potential could be explored by specific combinations of traits.

Spatial variation of climate and the impact of disturbances on local climate and forest recovery in northern Finland

The structure and function of northern ecosystems are strongly influenced by climate change and variability and by human-induced disturbances. The projected global change is likely to have a pronounced effect on the distribution and productivity of different species, generating large changes in the equilibrium at the tree-line. In turn, movement of the tree-line and the redistribution of species produce feedback to both the local and the regional climate. This research was initiated with the objective of examining the influence of natural conditions on the small-scale spatial variation of climate in Finnish Lapland, and to study the interaction and feedback mechanisms in the climate-disturbances-vegetation system near the climatological border of boreal forest. The high (1 km) resolution spatial variation of climate parameters over northern Finland was determined by applying the Kriging interpolation method that takes into account the effect of external forcing variables, i.e., geographical coordinates, elevation, sea and lake coverage. Of all the natural factors shaping the climate, the geographical position, local topography and altitude proved to be the determining ones. Spatial analyses of temperature- and precipitation-derived parameters based on a 30-year dataset (1971-2000) provide a detailed description of the local climate. Maps of the mean, maximum and minimum temperatures, the frost-free period and the growing season indicate that the most favourable thermal conditions exist in the south-western part of Lapland, around large water bodies and in the Kemijoki basin, while the coldest regions are in highland and fell Lapland. The distribution of precipitation is predominantly longitudinally dependent but with the definite influence of local features. The impact of human-induced disturbances, i.e., forest fires, on local climate and its implication for forest recovery near the northern timberline was evaluated in the Tuntsa area of eastern Lapland, damaged by a widespread forest fire in 1960 and suffering repeatedly-failed vegetation recovery since that. Direct measurements of the local climate and simulated heat and water fluxes indicated the development of a more severe climate and physical conditions on the fire-disturbed site. Removal of the original, predominantly Norway spruce and downy birch vegetation and its substitution by tundra vegetation has generated increased wind velocity and reduced snow accumulation, associated with a large variation in soil temperature and moisture and deep soil frost. The changed structural parameters of the canopy have determined changes in energy fluxes by reducing the latter over the tundra vegetation. The altered surface and soil conditions, as well as the evolved severe local climate, have negatively affected seedling growth and survival, leading to more unfavourable conditions for the reproduction of boreal vegetation and thereby causing deviations in the regional position of the timberline. However it should be noted that other factors, such as an inadequate seed source or seedbed, the poor quality of the soil and the intensive logging of damaged trees could also exacerbate the poor tree regeneration. In spite of the failed forest recovery at Tunsta, the position and composition of the timberline and tree-line in Finnish Lapland may also benefit from present and future changes in climate. The already-observed and the projected increase in temperature, the prolonged growing season, as well as changes in the precipitation regime foster tree growth and new regeneration, resulting in an advance of the timberline and tree-line northward and upward. This shift in the distribution of vegetation might be decelerated or even halted by local topoclimatic conditions and by the expected increase in the frequency of disturbances.

Increasing the productivity of avocado orchards using high-density plantings: A review

There is strong interest in the use of high-density plantings to increase the productivity of avocado (Persea americana) orchards. Close plantings have the potential for higher yields and returns than standard or traditional plantings, especially in the early years of production. The success of this technology is dependent on the use of methods to control shoot growth and maximise light interception as the trees begin to bear fruit. We reviewed the performance of high-density orchards in different environments, and the success of efforts to control the growth of the trees through the use of dwarfing material, canopy management and growth regulators. Close plantings generally produce higher yields in the first few years of bearing compared with the yields of standard plantings. However, in most growing areas, the trees in the close plantings soon begin to crowd each other and yields decline. This usually occurs despite efforts to control shoot growth by pruning the trees or by applying growth regulators. Efforts to breed dwarfing rootstocks that can control the growth of mature trees have been largely unsuccessful. In the absence of dwarfing material, effective canopy management appears to be the largest barrier to success of high-density orchards. Further research on the use of different pruning strategies and growth regulators to control the growth of the trees and maximise light interception is required. There are potential problems with some of the growth regulators persisting in the harvested fruit and soil under certain circumstances.

Resting sites, edge effects and dispersion of a polyphagous Bactrocera fruit fly within crops of different architecture

The spot or strip application of poisoned protein bait is a lure-and-kill technique used for the management of fruit flies. Knowledge of where flies occur in the crop environment is an important part of maximizing the efficacy of this tool. Bactrocera tryoni is a polyphagous pest of horticulture for which very little is known about its distribution within crops. With particular reference to edge effects, we monitored the abundance of B. tryoni in two crops of different architecture; strawberry and apple. In strawberries, we found more flies on the crop edge early in the fruiting season, which lessened gradually and eventually disappeared as the season progressed. In apple orchards, no such edge effect was observed and flies were found equally throughout the orchard. We postulated these differences may be due to differences in crop height (high vs. short) and/or crop canopy architecture (opened and branched in apple, dense and closed in strawberry). In a field cage trial, we tested these predictions using artificial plants of different height and canopy condition. Height and canopy structure type had no significant effects on fly oviposition and protein feeding, but the 'apple' type canopy significantly influenced resting. We thus postulate that there was an edge effect in strawberry because the crop was not providing resting sites and flies were doing so in vegetation around the field margins. The finding that B. tryoni shows different resting site preferences based on plant architecture offers the potential for strategic manipulation of the fly through specific border or inter-row plantings. © 2013 Blackwell Verlag GmbH.

Identifying the Function of Sorghum's Drought Tolerance Stay-Green QTL

The goal of this research is to understand the function of allelic variation of genes underpinning the stay-green drought adaptation trait in sorghum in order to enhance yield in water-limited environments. Stay-green, a delayed leaf senescence phenotype in sorghum, is primarily an emergent consequence of the improved balance between the supply and demand of water. Positional and functional fine-mapping of candidate genes associated with stay-green in sorghum is the focus of an international research partnership between Australian (UQ/DAFFQ) and US (Texas A&M University) scientists. Stay-green was initially mapped to four chromosomal regions (Stg1, Stg2, Stg3, and Stg4) by a number of research groups in the US and Australia. Physiological dissection of near-isolines containing single introgressions of Stg QTL (Stg1-4) indicate that these QTL reduce water demand before flowering by constricting the size of the canopy, thereby increasing water availability during grain filling and, ultimately, grain yield. Stg and root angle QTL are also co-located and, together with crop water use data, suggest the role of roots in the stay-green phenomenon. Candidate genes have been identified in Stg1-4, including genes from the PIN family of auxin efflux carriers in Stg1 and Stg2, with 10 of 11 PIN genes in sorghum co-locating with Stg QTL. Modified gene expression in some of these PIN candidates in the stay-green compared with the senescent types has been found in preliminary RNA expression profiling studies. Further proof-of-function studies are underway, including comparative genomics, SNP analysis to assess diversity at candidate genes, reverse genetics and transformation.

Improvement of mango tree architecture

This paper discusses the role of mango canopy architecture in mango productivity and orchard management and considers potential increases on production of high density orchards through improved canopy architecture. Lower tree height, reduced vigour and smaller more open canopies are recognised as important aspects of high density orchards. However, vigour management, light relations, flowering and crop load of high density orchards needs to be better understood if we are to developed sustainable highly productive canopy training and pruning systems that are easy to maintain at high planting densities.

Radiative transfer, interception and scattering in coniferous forests : models and applications for production ecology and remote sensing

This work develops methods to account for shoot structure in models of coniferous canopy radiative transfer. Shoot structure, as it varies along the light gradient inside canopy, affects the efficiency of light interception per unit needle area, foliage biomass, or foliage nitrogen. The clumping of needles in the shoot volume also causes a notable amount of multiple scattering of light within coniferous shoots. The effect of shoot structure on light interception is treated in the context of canopy level photosynthesis and resource use models, and the phenomenon of within-shoot multiple scattering in the context of physical canopy reflectance models for remote sensing purposes. Light interception. A method for estimating the amount of PAR (Photosynthetically Active Radiation) intercepted by a conifer shoot is presented. The method combines modelling of the directional distribution of radiation above canopy, fish-eye photographs taken at shoot locations to measure canopy gap fraction, and geometrical measurements of shoot orientation and structure. Data on light availability, shoot and needle structure and nitrogen content has been collected from canopies of Pacific silver fir (Abies amabilis (Dougl.) Forbes) and Norway spruce (Picea abies (L.) Karst.). Shoot structure acclimated to light gradient inside canopy so that more shaded shoots have better light interception efficiency. Light interception efficiency of shoots varied about two-fold per needle area, about four-fold per needle dry mass, and about five-fold per nitrogen content. Comparison of fertilized and control stands of Norway spruce indicated that light interception efficiency is not greatly affected by fertilization. Light scattering. Structure of coniferous shoots gives rise to multiple scattering of light between the needles of the shoot. Using geometric models of shoots, multiple scattering was studied by photon tracing simulations. Based on simulation results, the dependence of the scattering coefficient of shoot from the scattering coefficient of needles is shown to follow a simple one-parameter model. The single parameter, termed the recollision probability, describes the level of clumping of the needles in the shoot, is wavelength independent, and can be connected to previously used clumping indices. By using the recollision probability to correct for the within-shoot multiple scattering, canopy radiative transfer models which have used leaves as basic elements can use shoots as basic elements, and thus be applied for coniferous forests. Preliminary testing of this approach seems to explain, at least partially, why coniferous forests appear darker than broadleaved forests in satellite data.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.

Ecology, population genetics and conservation of the African violet

The ongoing rapid fragmentation of tropical forests is a major threat to global biodiversity. This is because many of the tropical forests are so-called biodiversity 'hotspots', areas that host exceptional species richness and concentrations of endemic species. Forest fragmentation has negative ecological and genetic consequences for plant survival. Proposed reasons for plant species' loss in forest fragments are, e.g., abiotic edge effects, altered species interactions, increased genetic drift, and inbreeding depression. To be able to conserve plants in forest fragments, the ecological and genetic processes that threaten the species have to be understood. That is possible only after obtaining adequate information on their biology, including taxonomy, life history, reproduction, and spatial and genetic structure of the populations. In this research, I focused on the African violet (genus Saintpaulia), a little-studied conservation flagship from the Eastern Arc Mountains and Coastal Forests hotspot of Tanzania and Kenya. The main objective of the research was to increase understanding of the life history, ecology and population genetics of Saintpaulia that is needed for the design of appropriate conservation measures. A further aim was to provide population-level insights into the difficult taxonomy of Saintpaulia. Ecological field work was conducted in a relatively little fragmented protected forest in the Amani Nature Reserve in the East Usambara Mountains, in northeastern Tanzania, complemented by population genetic laboratory work and ecological experiments in Helsinki, Finland. All components of the research were conducted with Saintpaulia ionantha ssp. grotei, which forms a taxonomically controversial population complex in the study area. My results suggest that Saintpaulia has good reproductive performance in forests with low disturbance levels in the East Usambara Mountains. Another important finding was that seed production depends on sufficient pollinator service. The availability of pollinators should thus be considered in the in situ management of threatened populations. Dynamic population stage structures were observed suggesting that the studied populations are demographically viable. High mortality of seedlings and juveniles was observed during the dry season but this was compensated by ample recruitment of new seedlings after the rainy season. Reduced tree canopy closure and substrate quality are likely to exacerbate seedling and juvenile mortality, and, therefore, forest fragmentation and disturbance are serious threats to the regeneration of Saintpaulia. Restoration of sufficient shade to enhance seedling establishment is an important conservation measure in populations located in disturbed habitats. Long-term demographic monitoring, which enables the forecasting of a population s future, is also recommended in disturbed habitats. High genetic diversities were observed in the populations, which suggest that they possess the variation that is needed for evolutionary responses in a changing environment. Thus, genetic management of the studied populations does not seem necessary as long as the habitats remain favourable for Saintpaulia. The observed high levels of inbreeding in some of the populations, and the reduced fitness of the inbred progeny compared to the outbred progeny, as revealed by the hand-pollination experiment, indicate that inbreeding and inbreeding depression are potential mechanisms contributing to the extinction of Saintpaulia populations. The relatively weak genetic divergence of the three different morphotypes of Saintpaulia ionantha ssp. grotei lend support to the hypothesis that the populations in the Usambara/lowlands region represent a segregating metapopulation (or metapopulations), where subpopulations are adapting to their particular environments. The partial genetic and phenological integrity, and the distinct trailing habit of the morphotype 'grotei' would, however, justify its placement in a taxonomic rank of its own, perhaps in a subspecific rank.

Dung beetle radiations in Madagascar

Speciation on islands is affected by island size and the range of habitats and resources available and often also by limited interactions with other taxa. An ancestral population may evolve into a large number of species via an adaptive radiation. In Madagascar, most groups of animals and plants have radiated on the island, having arrived via oceanic dispersal during the long isolation of Madagascar. Characteristic features of Malagasy biota are exceptionally high level of endemism, high species richness as well as lack of many higher taxa that are dominant on the African mainland. Malagasy dung beetles are dominated by two tribes, Canthonini and Helictopleurina, with more than 250 endemic species. In this thesis I have reconstructed molecular phylogenies for the two tribes using several gene regions and different phylogenetic methods. Evolution of closely related species and among populations of the same species was examined with haplotype networks. The Malagasy Canthonini consists of three large lineages, while Helictopleurina forms a monophyletic group. The ancestors of each of the four clades colonised Madagascar at different times during Cenozoic. The subsequent radiations differ in terms of the number of extant species (from 37 to more than 100) and the level of ecological differentiation. In addition, Onthophagini (6 species) and Scarabaeini (3) have colonised Madagascar several times, but they have not radiated and the few species have not entered forests where Canthonini and Helictopleurina mostly occur. Among the three Canthonini radiations, speciation appears to have been mostly allopatric in the oldest and the youngest clades, while in the Epactoides clade sister species have diverged in their ecologies but have similar geographical distributions, indicating that speciation may have occurred in regional sympatry. The most likely isolating mechanisms have been rivers and forest refugia during dry and cool geological periods. Most species are generalists feeding on both carrion and dung, and competition among ecologically similar species may prevent their coexistence in the same communities. Some species have evolved to forage in the canopy and a few species have shifted to use cattle dung, a new resource in the open habitats following the introduction of cattle 1500 years ago. The latter shift has allowed species to expand their geographical ranges.

Dark Mess

In a world consumed by quests for happiness and personal growth, Grant Stevens’ new exhibition, Dark Mess, delves into the psychic troubles that sometimes lie below the canopy. Working predominantly with video, photography and installation, Stevens’ practice explores how the verbal and non-verbal languages of popular screen culture interface with contemporary subjectivity. This exhibition continues Stevens’ interest in the natural environment as a catalyst and proxy for introspection and self-discovery. Pushing sound and image to distortion, Dark Mess offers a disquieting journey through the undergrowth.

Assessment of crop insect damage using unmanned aerial systems: A machine learning approach

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising technology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of the approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labeling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means. The outcome of this approach is a soft K-means algorithm similar to the EM algorithm for Gaussian mixture models. The results show the algorithm delivers decision boundaries that consistently classify the field into three clusters, one for each crop health level. The methodology presented in this paper represents a venue for further research towards automated crop damage assessments and biosecurity surveillance.