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.

Host selection and parasitism behavior of lysiphlebus testaceipes: Role of plant, aphid species and instar

The aphid parasitoid Lysiphlebus testaceipes is a potentially valuable biological control agent of Aphis gossypii a major worldwide pest of cotton. One means of increasing the abundance of a biological control agent is to provide an alternative host habitat adjacent to cropping, from which they can provide pest control services in the crop. Host selection and parasitism rate of an alternative host aphid, Aphis craccivora by L. testaceipes were studied in a series of experiments that tested its host suitability relative to A. gossypii on cotton, hibiscus and mungbean. Host acceptance, as measured by number of ovipositions was much greater in A. craccivora compared to A. gossypii, while more host aphids were accepted on mungbean than cotton. When given a choice L. testaceipes attacks more 4th instar and adult stages (63% and 70%, respectively) of both hosts than 2nd instar nymphs (47%). In a switching (host choice) experiment, L. testaceipes preferentially attacked A. craccivora on mungbean over A. gossypii on cotton. Observations of parasitoid contact with A. gossypii cornicle secretion suggest it provides a useful deterrent against parasitoid attack. From these experiments it appears L. testaceipes has a preference for A. craccivora and mungbean compared to A. gossypii and cotton, in this respect using A. craccivora and mungbean as alternative habitat may not work as the parasitoid is unlikely to switch away from its preferred host. © 2012.

Drought stress characterization of post-rainy season (rabi) sorghum in India

During the post-rainy (rabi) season in India around 3 million tonnes of sorghum grain is produced from 5.7 million ha of cropping. This underpins the livelihood of about 5 million households. Severe drought is common as the crop grown in these areas relies largely on soil moisture stored during the preceding rainy season. Improvement of rabi sorghum cultivars through breeding has been slow but could be accelerated if drought scenarios in the production regions were better understood. The sorghum crop model within the APSIM (Agricultural Production Systems sIMulator) platform was used to simulate crop growth and yield and the pattern of crop water status through each season using available historical weather data. The current model reproduced credibly the observed yield variation across the production region (R2=0.73). The simulated trajectories of drought stress through each crop season were clustered into five different drought stress patterns. A majority of trajectories indicated terminal drought (43%) with various timings of onset during the crop cycle. The most severe droughts (25% of seasons) were when stress began before flowering and resulted in failure of grain production in most cases, although biomass production was not affected so severely. The frequencies of drought stress types were analyzed for selected locations throughout the rabi tract and showed different zones had different predominating stress patterns. This knowledge can help better focus the search for adaptive traits and management practices to specific stress situations and thus accelerate improvement of rabi sorghum via targeted specific adaptation. The case study presented here is applicable to other sorghum growing environments. © 2012 Elsevier B.V.

A multisite managed environment facility for targeted trait and germplasm phenotyping

Field evaluation of germplasm for performance under water and heat stress is challenging. Field environments are variable and unpredictable, and genotype x environment interactions are difficult to interpret if environments are not well characterised. Numerous traits, genes and quantitative trait loci have been proposed for improving performance but few have been used in variety development. This reflects the limited capacity of commercial breeding companies to screen for these traits and the absence of validation in field environments relevant to breeding companies, and because little is known about the economic benefit of selecting one particular trait over another. The value of the proposed traits or genes is commonly not demonstrated in genetic backgrounds of value to breeding companies. To overcome this disconnection between physiological trait breeding and uptake by breeding companies, three field sites representing the main environment types encountered across the Australian wheatbelt were selected to form a set of managed environment facilities (MEFs). Each MEF manages soil moisture stress through irrigation, and the effects of heat stress through variable sowing dates. Field trials are monitored continuously for weather variables and changes in soil water and canopy temperature in selected probe genotypes, which aids in decisions guiding irrigation scheduling and sampling times. Protocols have been standardised for an essential core set of measurements so that phenotyping yield and other traits are consistent across sites and seasons. MEFs enable assessment of a large number of traits across multiple genetic backgrounds in relevant environments, determine relative trait value, and facilitate delivery of promising germplasm and high value traits into commercial breeding programs.

A participatory whole farm modelling approach to understand impacts and increase preparedness to climate change in Australia

This study presents the use of a whole farm model in a participatory modelling research approach to examine the sensitivity of four contrasting case study farms to a likely climate change scenario. The newly generated information was used to support discussions with the participating farmers in the search for options to design more profitable and sustainable farming systems in Queensland Australia. The four case studies contrasted in key systems characteristics: opportunism in decision making, i.e. flexible versus rigid crop rotations; function, i.e. production of livestock or crops; and level of intensification, i.e. dryland versus irrigated agriculture. Tested tactical and strategic changes under a baseline and climate change scenario (CCS) involved changes in the allocation of land between cropping and grazing enterprises, alternative allocations of limited irrigation water across cropping enterprises, and different management rules for planting wheat and sorghum in rainfed cropping. The results show that expected impacts from a likely climate change scenario were evident in the following increasing order: the irrigated cropping farm case study, the cropping and grazing farm, the more opportunistic rainfed cropping farm and the least opportunistic rainfed cropping farm. We concluded that in most cases the participating farmers were operating close to the efficiency frontier (i.e. in the relationship between profits and risks). This indicated that options to adapt to climate change might need to evolve from investments in the development of more innovative cropping and grazing systems and/or transformational changes on existing farming systems. We expect that even though assimilating expected changes in climate seems to be rather intangible and premature for these farmers, as innovations are developed, adaptation is likely to follow quickly. The multiple interactions among farm management components in complex and dynamic farm businesses operating in a variable and changing climate, make the use of whole farm participatory modelling approaches valuable tools to quantify benefits and trade-offs from alternative farming systems designs in the search for improved profitability and resilience.

Weed age affects chemical control of Conyza bonariensis in fallows

In the last decade, Conyza bonariensis has become a widespread and difficult-to-control weed in Australian broad-acre cropping, particularly in glyphosate-based zero-tilled fallows of the subtropical grain region. The first Australian populations of C. bonariensis, where it is known as flaxleaf fleabane, were confirmed resistant to glyphosate in 2010. Control with alternative herbicides in fallows has been inconsistent, with earlier research indicating that weed age could be a potential contributing factor. In two field experiments, the impact of weed age (one, two and three months) was measured on the efficacy of six non-selective herbicide mixtures and sequential applications for control in fallows. In another two experiments we evaluated 11 non-selective herbicides, mixtures and sequential applications applied to one and three month old weeds using higher rates on older weeds. When herbicide rates were consistent for different weed ages, efficacy was reduced only by an average of 1% when two month old weeds were treated compared to one month old weeds. However when applied to three month old weeds, efficacy of treatments was significantly (P < 0.001) reduced by 3-30%. When herbicide rates were increased, weed age had no adverse effect on efficacy, which ranged from 90 to 100%, for amitrole, glyphosate mixed with 2,4-D amine plus picloram, and three sequential application treatments of glyphosate mixtures followed with bipyridyl products. Thus, this problem weed can be controlled effectively and consistently at the rosette stage of one to two months old, or three month old weeds with several different treatments at robust rates. These effective glyphosate alternatives and sequential-application tactics will minimise replenishment of the soil seed-bank and further reduce the risk for further evolution of glyphosate resistance. (C) 2012 Elsevier Ltd. All rights reserved.

Biological control of Mikania micrantha in Papua New Guinea and Fiji using the rust fungus Puccinia spegazzinii

Mikania micrantha Kunth (Asteraceae), commonly known as ‘mile-a-minute’, is a neotropical plant species now found in 17 Pacific island countries and territories, invading small cropping areas and plantations, thereby reducing productivity and food security. In 2006, a biocontrol project on M. micrantha commenced in Fiji and Papua New Guinea (PNG). The distribution of M. micrantha as well as baseline data such as plant growth rates and socio-economic impacts were determined before the importation of any biocontrol agents. Mikania micrantha was recorded in all 15 lowland provinces in PNG and on all major islands in Fiji. Plants grow about 3.2cm/day in PNG and about 1.9cm/day in Fiji. A socio-economic survey, involving over 370 respondents in over 220 villages from 15 provinces in PNG, found that 78% of respondents considered M. micrantha a serious weed and about 44% had M. micrantha, which they needed to weed at least fortnightly, in over a third of their land. Over 80% of respondents used slashing and/or handpulling as the preferred method of weed control. About 40% of respondents considered that M. micrantha reduced crop yield by more than 30%. In Fiji, 52 respondents from four islands participated in the survey. Over 60% of respondents in Fiji considered M. micrantha a serious weed and 23% had about 30% of their farm lands infested with the weed. Only 15% of respondents needed to weed at least fortnightly, with 56% using slashing and/or hand-pulling as the preferred means of control. Over 65% of respondents estimated that they lost at least 30% of potential crop yield to M. micrantha. Nearly 90% of respondents used M. micrantha as a medicinal plant to treat cuts and wounds. The life history of the rust Puccinia spegazzinii de Toni (Pucciniales: Pucciniaceae), originating from Ecuador, and imported into PNG and Fiji in 2008, was studied. P. spegazzinii is a microcyclic and autoecious rust and has a life cycle of 18-22 days. An efficient culturing and field release method was developed. Since 2008, the rust has been released at over 450 sites in 15 provinces in PNG, establishing at nearly 70 sites in four provinces. From some sites, the rust has spread over 7 km in 12 months. In Fiji, the rust has been released at over 80 sites, on four of the main islands, namely Viti Levu, Vanua Levu, Taveuni and Ovalau, and has established at 20 sites on Viti Levu and Vanua Levu. Plant growth studies and field monitoring in PNG showed that P. spegazzinii can significantly reduce the growth and density of M. micrantha and offers great potential for the control of this weed.

Soil nitrogen—crop response calibration relationships and criteria for winter cereal crops grown in Australia

More than 1200 wheat and 120 barley experiments conducted in Australia to examine yield responses to applied nitrogen (N) fertiliser are contained in a national database of field crops nutrient research (BFDC National Database). The yield responses are accompanied by various pre-plant soil test data to quantify plant-available N and other indicators of soil fertility status or mineralisable N. A web application (BFDC Interrogator), developed to access the database, enables construction of calibrations between relative crop yield ((Y0/Ymax) × 100) and N soil test value. In this paper we report the critical soil test values for 90% RY (CV90) and the associated critical ranges (CR90, defined as the 70% confidence interval around that CV90) derived from analysis of various subsets of these winter cereal experiments. Experimental programs were conducted throughout Australia’s main grain-production regions in different eras, starting from the 1960s in Queensland through to Victoria during 2000s. Improved management practices adopted during the period were reflected in increasing potential yields with research era, increasing from an average Ymax of 2.2 t/ha in Queensland in the 1960s and 1970s, to 3.4 t/ha in South Australia (SA) in the 1980s, to 4.3 t/ha in New South Wales (NSW) in the 1990s, and 4.2 t/ha in Victoria in the 2000s. Various sampling depths (0.1–1.2 m) and methods of quantifying available N (nitrate-N or mineral-N) from pre-planting soil samples were used and provided useful guides to the need for supplementary N. The most regionally consistent relationships were established using nitrate-N (kg/ha) in the top 0.6 m of the soil profile, with regional and seasonal variation in CV90 largely accounted for through impacts on experimental Ymax. The CV90 for nitrate-N within the top 0.6 m of the soil profile for wheat crops increased from 36 to 110 kg nitrate-N/ha as Ymax increased over the range 1 to >5 t/ha. Apparent variation in CV90 with seasonal moisture availability was entirely consistent with impacts on experimental Ymax. Further analyses of wheat trials with available grain protein (~45% of all experiments) established that grain yield and not grain N content was the major driver of crop N demand and CV90. Subsets of data explored the impact of crop management practices such as crop rotation or fallow length on both pre-planting profile mineral-N and CV90. Analyses showed that while management practices influenced profile mineral-N at planting and the likelihood and size of yield response to applied N fertiliser, they had no significant impact on CV90. A level of risk is involved with the use of pre-plant testing to determine the need for supplementary N application in all Australian dryland systems. In southern and western regions, where crop performance is based almost entirely on in-crop rainfall, this risk is offset by the management opportunity to split N applications during crop growth in response to changing crop yield potential. In northern cropping systems, where stored soil moisture at sowing is indicative of minimum yield potential, erratic winter rainfall increases uncertainty about actual yield potential as well as reducing the opportunity for effective in-season applications.

Soil phosphorus–crop response calibration relationships and criteria for winter cereal crops grown in Australia

Soil testing is the most widely used tool to predict the need for fertiliser phosphorus (P) application to crops. This study examined factors affecting critical soil P concentrations and confidence intervals for wheat and barley grown in Australian soils by interrogating validated data from 1777 wheat and 150 barley field treatment series now held in the BFDC National Database. To narrow confidence intervals associated with estimated critical P concentrations, filters for yield, crop stress, or low pH were applied. Once treatment series with low yield (<1 t/ha), severe crop stress, or pHCaCl2 <4.3 were screened out, critical concentrations were relatively insensitive to wheat yield (>1 t/ha). There was a clear increase in critical P concentration from early trials when full tillage was common compared with those conducted in 1995–2011, which corresponds to a period of rapid shift towards adoption of minimum tillage. For wheat, critical Colwell-P concentrations associated with 90 or 95% of maximum yield varied among Australian Soil Classification (ASC) Orders and Sub-orders: Calcarosol, Chromosol, Kandosol, Sodosol, Tenosol and Vertosol. Soil type, based on ASC Orders and Sub-orders, produced critical Colwell-P concentrations at 90% of maximum relative yield from 15 mg/kg (Grey Vertosol) to 47 mg/kg (Supracalcic Calcarosols), with other soils having values in the range 19–27 mg/kg. Distinctive differences in critical P concentrations were evident among Sub-orders of Calcarosols, Chromosols, Sodosols, Tenosols, and Vertosols, possibly due to differences in soil properties related to P sorption. However, insufficient data were available to develop a relationship between P buffering index (PBI) and critical P concentration. In general, there was no evidence that critical concentrations for barley would be different from those for wheat on the same soils. Significant knowledge gaps to fill to improve the relevance and reliability of soil P testing for winter cereals were: lack of data for oats; the paucity of treatment series reflecting current cropping practices, especially minimum tillage; and inadequate metadata on soil texture, pH, growing season rainfall, gravel content, and PBI. The critical concentrations determined illustrate the importance of recent experimental data and of soil type, but also provide examples of interrogation pathways into the BFDC National Database to extract locally relevant critical P concentrations for guiding P fertiliser decision-making in wheat and barley.

Integrating organic matter into banana plantation in North Queensland: the effects on soil properties

The major banana production areas in Australia are particularly sensitive to environments due to their close proximity to areas of World Heritage rainforest and the Great Barrier Reef catchment. Management of soil quality, nutrients and pesticides are vital to maintaining the integrity of these sensitive areas. Studies on cropping systems have suggested that integrating organic matter into ground cover management would improve the quality of soil under banana cultivation. In this study, an alternative management practice for bananas, which addresses the management of organic matter and fertiliser application, was assessed and compared to the conventional practice currently employed in the banana industry. Several chemical, physical and biological soil parameters were measured including: pH, electrical conductivity, water stable aggregates, bulk density, water filled pore space, porosity, water content, fluorescein diacetate hydrolyis (FDA) and beta-glucosidase activity. The alternative management practice did not have a significant impact of the production and growth of bananas but overall improved the quality of the soil. Although some differences were observed, the chemical and physical soil characteristics did not differ dramatically between the two management systems. The addition of organic matter resulted in the soil under alternative practice having higher FDA and beta-glucosidase levels, indicating higher microbial activity. The integration of organic matter into the management of bananas resulted in positive benefits on soil properties under bananas, however, methods of maintaining organic matter in the soil need to be further researched.

The avocado problem solver field guide

This guide has been produced to assist Australian avocado growers and others involved in the avocado supply chain to identify the wide range of pests, diseases, nutrient deficiencies and toxicitites, and other disorders that may affect orchards and the quality of fruit reaching the consumer