Environment characterization as an aid to wheat improvement: interpreting genotype-environment interactions by modelling water-deficit patterns in North-Eastern Australia.

Genotype-environment interactions (GEI) limit genetic gain for complex traits such as tolerance to drought. Characterization of the crop environment is an important step in understanding GEI. A modelling approach is proposed here to characterize broadly (large geographic area, long-term period) and locally (field experiment) drought-related environmental stresses, which enables breeders to analyse their experimental trials with regard to the broad population of environments that they target. Water-deficit patterns experienced by wheat crops were determined for drought-prone north-eastern Australia, using the APSIM crop model to account for the interactions of crops with their environment (e.g. feedback of plant growth on water depletion). Simulations based on more than 100 years of historical climate data were conducted for representative locations, soils, and management systems, for a check cultivar, Hartog. The three main environment types identified differed in their patterns of simulated water stress around flowering and during grain-filling. Over the entire region, the terminal drought-stress pattern was most common (50% of production environments) followed by a flowering stress (24%), although the frequencies of occurrence of the three types varied greatly across regions, years, and management. This environment classification was applied to 16 trials relevant to late stages testing of a breeding programme. The incorporation of the independently-determined environment types in a statistical analysis assisted interpretation of the GEI for yield among the 18 representative genotypes by reducing the relative effect of GEI compared with genotypic variance, and helped to identify opportunities to improve breeding and germplasm-testing strategies for this region.

Maximising profitability with limited water in cotton farming systems

Diminishing water supply, changing weather patterns and pressure to enhance environmental flows are making it imperative to optimise water use efficiency (WUE) on cotton/grain farming systems. Growers are looking for better strategies to make the best use of limited water, but it is still not clear how to best use the available water at farm and field scale. This research project investigated the impact of management strategies to deal with limited water supplies on the yield and quality of irrigated cotton and wheat. The objectives were: (1) to develop irrigation management guidelines for the main irrigated crops on the Darling Downs for full- and deficitirrigation scenarios, taking into account the critical factors that affect irrigation decisions at the local level, (2) to quantify the evapotranspiration (ET) of Bollgard II cotton and wheat and its relationship to yield and quality under full- and deficit-irrigation scenarios, and (3) to increase industry awareness and education of farming systems practises for optimised economic water use efficiency.Objective (1) was addressed by (A) collaborating with ASPRU to develop the APSFarm model within APSIM to be able to perform multi-paddock simulations. APSFarm was then tested by conducting a case study at a farm near Dalby, and (B) conducting semi-structured interviews with individual farmers and crop consultants on the Darling Downs to document the strategies they are using to deal with limited water. Objective (2) was addressed by (A) building and installing 12 large (1 m x 1m x 1.5 m) weighing lysimeters to measure crop evapotranspiration. The lysimeters were installed at the Agri-Science Queensland research station at Kingsthorpe in November 2008, (B) conducting field experiments to measure crop evapotranspiration and crop development under four irrigation treatments, including dryland, deficit-irrigation, and full irrigation. Field experiments were conducted with cotton in 2007-08 and 2008-09, and with wheat in 2008 and 2009, and (C) collaborating with USQ on a PhD thesis to quantify the impact of crop stress on crop evapotranspiration and canopy temperature. Glasshouse experiments were conducted with wheat in 2008 and with cotton in 2008-09. Objective (3) was addressed by (A) conducting a field day at Kingsthorpe in 2009, which was attended by 80 participants, (B) presenting information in conferences in Australia and overseas, (D) presenting information at farmers meeting, (E) making presentations to crop consultants, and (F) preparing extension publications.As part of this project we contributed to the development of APSfarm, which has been successfully applied to evaluate the feasibility of practices at the whole-farm scale. From growers and crop consultants interviews we learned that there is a great variety of strategies, at different scales, that they are using to deal with limited water situation. These strategies will be summarised in the "e;Limited Water Guidelines for the Darling Downs"e; that we are currently preparing. As a result of this project, we now have a state-of-the-art lysimeter research facility (23 large weighing lysimeters) to be able to conduct replicated experiments to investigate daily water use of a variety of crops under different irrigation regimes and under different environments. Under this project, a series of field and glasshouse experiments were conducted with cotton and wheat, investigating aspects like: (A) quantification of daily and seasonal crop water use under nonstressed and stressed conditions, (B) impact of row configuration on crop water use, (C) impact of water stress on yield, evapotranspiration, crop vegetative and reproductive development, soil water extraction pattern, yield and yield quality. The information obtained from this project is now being used to develop web-based tools to help growers make planning and day-to-day irrigation decisions.

Isohydric and anisohydric characterisation of vegetable crops. The classification of vegetables by their physiological responses to water stress

Research on the physiological response of crop plants to drying soils and subsequent water stress has grouped plant behaviours as isohydric and anisohydric. Drying soil conditions, and hence declining soil and root water potentials, cause chemical signals—the most studied being abscisic acid (ABA)—and hydraulic signals to be transmitted to the leaf via xylem pathways. Researchers have attempted to allocate crops as isohydric or anisohydric. However, different cultivars within crops, and even the same cultivars grown in different environments/climates, can exhibit both response types. Nevertheless, understanding which behaviours predominate in which crops and circumstances may be beneficial. This paper describes different physiological water stress responses, attempts to classify vegetable crops according to reported water stress responses, and also discusses implications for irrigation decision-making.

Water and thermal regimes for field pea in Australia and their implications for breeding.

There is a large gap between the refined approaches to characterise genotypes and the common use of location and season as a coarse surrogate for environmental characterisation of breeding trials. As a framework for breeding, the aim of this paper is quantifying the spatial and temporal patterns of thermal and water stress for field pea in Australia. We compiled a dataset for yield of the cv. Kaspa measured in 185 environments, and investigated the associations between yield and seasonal patterns of actual temperature and modelled water stress. Correlations between yield and temperature indicated two distinct stages. In the first stage, during crop establishment and canopy expansion before flowering, yield was positively associated with minimum temperature. Mean minimum temperature below similar to 7 degrees C suggests that crops were under suboptimal temperature for both canopy expansion and radiation-use efficiency during a significant part of this early growth period. In the second stage, during critical reproductive phases, grain yield was negatively associated with maximum temperature over 25 degrees C. Correlations between yield and modelled water supply/demand ratio showed a consistent pattern with three phases: no correlation at early stages of the growth cycle, a progressive increase in the association that peaked as the crop approached the flowering window, and a progressive decline at later reproductive stages. Using long-term weather records (1957-2010) and modelled water stress for 104 locations, we identified three major patterns of water deficit nation wide. Environment type 1 (ET1) represents the most favourable condition, with no stress during most of the pre-flowering phase and gradual development of mild stress after flowering. Type 2 is characterised by increasing water deficit between 400 degree-days before flowering and 200 degree-days after flowering and rainfall that relieves stress late in the season. Type 3 represents the more stressful condition with increasing water deficit between 400 degree-days before flowering and maturity. Across Australia, the frequency of occurrence was 24% for ET1, 32% for ET2 and 43% for ET3, highlighting the dominance of the most stressful condition. Actual yield averaged 2.2 t/ha for ET1, 1.9 t/ha for ET2 and 1.4 t/ha for ET3, and the frequency of each pattern varied substantially among locations. Shifting from a nominal (i.e. location and season) to a quantitative (i.e. stress type) characterisation of environments could help improving breeding efficiency of field pea in Australia.

Characterization of north-eastern Australian environments using APSIM for increasing rainfed maize production

Recurring water stresses are a major risk factor for rainfed maize cropping across the highly diverse agro-ecological environments of Queensland (Qld) and northern New South Wales (NNSW). Enhanced understanding of such agro-ecological diversity is necessary to more consistently sample target production environments for testing and targeting release of improved germplasm, and to improve the efficiency of the maize pre-breeding and breeding programs of Qld and New South Wales. Here, we used the Agricultural Production Systems Simulator (APSIM) – a well validated maize crop model to characterize the key distinctive water stress patterns and risk to production across the main maize growing regions of Qld and NNSW located between 15.8° and 31.5°S, and 144.5° and 151.8°E. APSIM was configured to simulate daily water supply demand ratios (SDRs) around anthesis as an indicator of the degree of water stress, and the final grain yield. Simulations were performed using daily climatic records during the period between 1890 and 2010 for 32 sites-soils in the target production regions. The runs were made assuming adequate nitrogen supply for mid-season maize hybrid Pioneer 3153. Hierarchical complete linkage analyses of the simulated yield resulted in five major clusters showing distinct probability distribution of the expected yields and geographic patterns. The drought stress patterns and their frequencies using SDRs were quantified using multivariate statistical methods. The identified stress patterns included no stress, mid-season (flowering) stress, and three terminal stresses differing in terms of severity. The combined frequency of flowering and terminal stresses was highest (82.9%), mainly in sites-soils combinations in the west of Qld and NNSW. Yield variability across the different sites-soils was significantly related to the variability in frequencies of water stresses. Frequencies of water stresses within each yield cluster tended to be similar, but different across clusters. Sites-soils falling within each yield cluster therefore could be treated as distinct maize production environments for testing and targeting newly developed maize cultivars and hybrids for adaptation to water stress patterns most common to those environments.

Developmental and growth controls of tillering and water-soluble carbohydrate accumulation in contrasting wheat (Triticum aestivum L.) genotypes: can we dissect them?

In wheat, tillering and water-soluble carbohydrates (WSCs) in the stem are potential traits for adaptation to different environments and are of interest as targets for selective breeding. This study investigated the observation that a high stem WSC concentration (WSCc) is often related to low tillering. The proposition tested was that stem WSC accumulation is plant density dependent and could be an emergent property of tillering, whether driven by genotype or by environment. A small subset of recombinant inbred lines (RILs) contrasting for tillering was grown at different plant densities or on different sowing dates in multiple field experiments. Both tillering and WSCc were highly influenced by the environment, with a smaller, distinct genotypic component; the genotypeenvironment range covered 350750 stems m(2) and 25210mg g(1) WSCc. Stem WSCc was inversely related to stem number m(2), but genotypic rankings for stem WSCc persisted when RILs were compared at similar stem density. Low tilleringhigh WSCc RILs had similar leaf area index, larger individual leaves, and stems with larger internode cross-section and wall area when compared with high tilleringlow WSCc RILs. The maximum number of stems per plant was positively associated with growth and relative growth rate per plant, tillering rate and duration, and also, in some treatments, with leaf appearance rate and final leaf number. A common threshold of the red:far red ratio (0.390.44; standard error of the difference0.055) coincided with the maximum stem number per plant across genotypes and plant densities, and could be effectively used in crop simulation modelling as a ocut-off' rule for tillering. The relationship between tillering, WSCc, and their component traits, as well as the possible implications for crop simulation and breeding, is discussed.

Interaction between production characteristics and postharvest performance and practices for fresh fruit

Significant interactions have been demonstrated between production factors and postharvest quality of fresh fruit. Accordingly, there is an attendant need for adaptive postharvest actions to modulate preharvest effects. The most significant preharvest effects appear to be mediated through mineral nutrition influences on the physical characteristics of fruit. Examples of specific influencers include fertilisers, water availability, rootstock, and crop load effects on fruit quality attributes such as skin colour, susceptibility to diseases and physiological disorders, and fruit nutritional composition. Also, rainfall before and during harvest can markedly affect fruit susceptibility to skin blemishes, physical damage, and diseases. Knowledge of preharvest-postharvest interactions can help determine the basis for variability in postharvest performance and thereby allow refinement of postharvest practices to minimise quality loss after harvest. This knowledge can be utilised in predictive management systems. Such systems can benefit from characterisation of fruit nutritional status, particularly minerals, several months before and/or at harvest to allow informed decisions on postharvest handling and marketing options. Other examples of proactive management practices include adjusting harvesting and packing systems to account for rainfall effects before and/or during harvest. Improved understanding of preharvest-postharvest interactions is contributing to the delivery of consistently higher quality of fruit to consumers. This paper focuses on the state of knowledge for sub-tropical and tropical fruits, in particular avocado and mango.

Interaction between production characteristics and postharvest performance and practices for fresh fruit

Significant interactions have been demonstrated between production factors and postharvest quality of fresh fruit. Accordingly, there is an attendant need for adaptive postharvest actions to modulate preharvest effects. The most significant preharvest effects appear to be mediated through mineral nutrition influences on the physical characteristics of fruit. Examples of specific influencers include fertilisers, water availability, rootstock, and crop load effects on fruit quality attributes such as skin colour, susceptibility to diseases and physiological disorders, and fruit nutritional composition. Also, rainfall before and during harvest can markedly affect fruit susceptibility to skin blemishes, physical damage, and diseases. Knowledge of preharvest-postharvest interactions can help determine the basis for variability in postharvest performance and thereby allow refinement of postharvest practices to minimise quality loss after harvest. This knowledge can be utilised in predictive management systems. Such systems can benefit from characterisation of fruit nutritional status, particularly minerals, several months before and/or at harvest to allow informed decisions on postharvest handling and marketing options. Other examples of proactive management practices include adjusting harvesting and packing systems to account for rainfall effects before and/or during harvest. Improved understanding of preharvest-postharvest interactions is contributing to the delivery of consistently higher quality of fruit to consumers. This paper focuses on the state of knowledge for sub-tropical and tropical fruits, in particular avocado and mango.

Stay-green alleles individually enhance grain yield in sorghum under drought by modifying canopy development and water uptake patterns

* Stay-green is an integrated drought adaptation trait characterized by a distinct green leaf phenotype during grain filling under terminal drought. We used sorghum (Sorghum bicolor), a repository of drought adaptation mechanisms, to elucidate the physiological and genetic mechanisms underpinning stay-green. * Near-isogenic sorghum lines (cv RTx7000) were characterized in a series of field and managed-environment trials (seven experiments and 14 environments) to determine the influence of four individual stay-green (Stg1–4) quantitative trait loci (QTLs) on canopy development, water use and grain yield under post-anthesis drought. * The Stg QTL decreased tillering and the size of upper leaves, which reduced canopy size at anthesis. This reduction in transpirational leaf area conserved soil water before anthesis for use during grain filling. Increased water uptake during grain filling of Stg near-isogenic lines (NILs) relative to RTx7000 resulted in higher post-anthesis biomass production, grain number and yield. Importantly, there was no consistent yield penalty associated with the Stg QTL in the irrigated control. * These results establish a link between the role of the Stg QTL in modifying canopy development and the subsequent impact on crop water use patterns and grain yield under terminal drought.

Variation in water extraction with maize plant density and its impact on model application

The use of maize simulation models to determine the optimum plant population for rainfed environments allows the evaluation of plant populations over multiple years and locations at a lower cost than traditional field experimentation. However the APSIM maize model that has been used to conduct some of these 'virtual' experiments assumes that the maximum rate of soil water extraction by the crop root system is constant across plant populations. This untested assumption may cause grain yield to be overestimated in lower plant populations. A field experiment was conducted to determine whether maximum rates of water extraction vary with plant population, and the maximum rate of soil water extraction was estimated for three plant populations (2.4, 3.5 and 5.5 plants m(-2)) under water limited conditions. Maximum soil water extraction rates in the field experiment decreased linearly with plant population, and no difference was detected between plant populations for the crop lower limit of soil water extraction. Re-analysis of previous maize simulation experiments demonstrated that the use of inappropriately high extraction-rate parameters at low plant populations inflated predictions of grain yield, and could cause erroneous recommendations to be made for plant population. The results demonstrate the importance of validating crop simulation models across the range of intended treatments. (C) 2013 Elsevier E.V. All rights reserved.

Physiological basis of yield variation in response to row spacing and plant density of mungbean grown in subtropical environments

In this study, we investigated the extent and physiological bases of yield variation due to row spacing and plant density configuration in the mungbean Vigna radiata (L.) Wilczek variety “Crystal” grown in different subtropical environments. Field trials were conducted in six production environments; one rain-fed and one irrigated trial each at Biloela and Emerald, and one rain-fed trial each at Hermitage and Kingaroy sites in Queensland, Australia. In each trial, six combinations of spatial arrangement of plants, achieved through two inter-row spacings of 1 m or 0.9 m (wide row), 0.5 m or 0.3 m (narrow row), with three plant densities, 20, 30 and 40 plants/m2, were compared. The narrow row spacing resulted in 22% higher shoot dry matter and 14% more yield compared to the wide rows. The yield advantage of narrow rows ranged from 10% to 36% in the two irrigated and three rain-fed trials. However, yield loss of up to 10% was also recorded from narrow rows at Emerald where the crop suffered severe drought. Neither the effects of plant density, nor the interaction between plant density and row spacing, however, were significant in any trial. The yield advantage of narrow rows was related to 22% more intercepted radiation. In addition, simulations by the Agricultural Production Systems Simulator model, using site-specific agronomy, soil and weather information, suggested that narrow rows had proportionately greater use of soil water through transpiration, compared to evaporation resulting in higher yield per mm of soil water. The long-term simulation of yield probabilities over 123 years for the two row configurations showed that the mungbean crop planted in narrow rows could produce up to 30% higher grain yield compared to wide rows in 95% of the seasons.

Water activity of poultry litter: Relationship to moisture content during a grow-out

Poultry grown on litter floors are in contact with their own waste products. The waste material needs to be carefully managed to reduce food safety risks and to provide conditions that are comfortable and safe for the birds. Water activity (Aw) is an important thermodynamic property that has been shown to be more closely related to microbial, chemical and physical properties of natural products than moisture content. In poultry litter, Aw is relevant for understanding microbial activity; litter handling and rheological properties; and relationships between in-shed relative humidity and litter moisture content. We measured the Aw of poultry litter collected throughout a meat chicken grow-out (from fresh pine shavings bedding material to day 52) and over a range of litter moisture content (10–60%). The Aw increased non-linearly from 0.71 to 1.0, and reached a value of 0.95 when litter moisture content was only 22–33%. Accumulation of manure during the grow-out reduced Aw for the same moisture content. These results are relevant for making decisions regarding litter re-use in multiple grow-outs as well as setting targets for litter moisture content to minimise odour, microbial risks and to ensure necessary litter physical conditions are maintained during a grow-out. Methods to predict Aw in poultry litter from moisture content are proposed.