Integrated crop management for brassica production

Early season beneficials in brassica crops.

Better Macadamia Crop Forecasting - Part 2

The continually expanding macadamia industry needs an accurate crop forecasting system to allow it to develop effective crop handling and marketing strategies, particularly when the industry faces recurring cycles of unsustainably high and low commodity prices. This project aims to provide the AMS with a robust, reliable predictive model of national crop volume within 10% of the actual crop by 1 April each year by factoring known seasonal, environmental, cultural, climatic, management and biological constraints, together with the existing AMS database which includes data on tree numbers, tree age, variety, location and previous season's production.

Relocation of intensive crop production systems to northern Australia

To adapt to climate variability and a lack of irrigation water, businesses and growers in southern Australia, northern New South Wales and southern Queensland are, or are considering, migrating their businesses to northern Australia.

ACIAR Integrated crop production of bananas

Integrated crop production of bananas to manage wilt diseases for improved livelihoods in Indonesia and Australia.

GRDC Improving crop and farm water use efficiency in Australia

Project Objectives: 1. Improving yield and water use efficiency of the wheat crop, the backbone of the Australia grains industry, by better matching management, variety, soil and climate. The aim is thus increasing kg grain/ha per mm evapotranspiration and kg grain/ha per mm rain. 2. Improving land and water productivity and profit by better arrangement of the components of the cropping system. This involves better allocation of farm resources (land, water, machinery, labour) and identifying strategies that account for trade-offs between profit and risk. The aim is thus improving $/ha per year and mm rain in a risk framework.

Better integration of crop-legume sequencing under limited water

It is proposed that over 4-5 years of study period, multiple collaborative sites will be established with on-farm cooperators to demonstrate better integration of crop-legume sequencing for improved root growth and functioning under limited water, leading to improved productivity and carbon sequestration, and reduced runoff and deep drainage losses.

Crop sequences to manage soil pathogens and increase northern grain production

This is part of a GRDC funded project led by Dr Jeremy Whish of CSIRO Ecosystem Sciences. The project aims to build a root-lesion nematode module into the crop growth simulation program APSIM (Agricultural Production Systems Simulator). This will utilise existing nematode and crop data from field, glasshouse and laboratory research led by Dr John Thompson. New data will be collected to validate and extend the model.

Optimising crop and economic performance of precision overhead irrigation

This project aims to develop integrated irrigation and nutrition management strategies under limited water for irrigators currently investing in overhead irrigation systems (CPLM) to minimize the learning lag in their use and optimize crop and economic performance.

Integrating crop improvement technologies for rapid genetic advance

This project developed a novel approach to integrating enhanced gene mapping technologies with crop modelling to enhance the rate of improvement in sorghum yield.

ACIAR Feasibility of farmers managing climate related crop production risk in India

Validation of new Indian seasonal climate forecasting products. In the Indian state of Andhra Pradesh (AP) kharif crops are heavily dependent on summer monsoon rains, where the timing and intensity of the rains affects crop yield. The majority of farms in AP are small and marginal, making them very vulnerable to yield reductions. Farmers also lack access to relevant information that might enable them to respond to seasonal conditions. Enabling farmers to utilise seasonal climate forecasting would allow them to respond to seasonal variability. To do this, farmers need a forecasting system that indicates a specific management strategy for the upcoming season, and effective and timely communication of the forecast information. Current agro-meteorological advisories in AP are issued on a bi-weekly basis, and they are relevant to an agro-climatic zone scale which may not be sufficiently relevant at a village level. Also, the information in the advisories may not be necessarily packaged in way relevant to cropping decisions by farmers. The objectives of this project are to evaluate the skill of seasonal climate forecasts to be issued for the 2008 monsoon season, to assess crop management options in response to seasonal scenarios that capture the range of seasonal climatic variability, to develop and evaluate options for effective communication and adoption of climate forecasts and agricultural advisories, and to synthesise and report on options for future research investments into seasonal climate forecasting.

Integrating sorghum whole genome sequence information with a compendium of sorghum QTL studies reveals uneven distribution of QTL and of gene-rich regions with significant implications for crop improvement.

A comprehensive analysis was conducted using 48 sorghum QTL studies published from 1995 to 2010 to make information from historical sorghum QTL experiments available in a form that could be more readily used by sorghum researchers and plant breeders. In total, 771 QTL relating to 161 unique traits from 44 studies were projected onto a sorghum consensus map. Confidence intervals (CI) of QTL were estimated so that valid comparisons could be made between studies. The method accounted for the number of lines used and the phenotypic variation explained by individual QTL from each study. In addition, estimated centimorgan (cM) locations were calculated for the predicted sorghum gene models identified in Phytozome (JGI GeneModels SBI v1.4) and compared with QTL distribution genome-wide, both on genetic linkage (cM) and physical (base-pair/bp) map scales. QTL and genes were distributed unevenly across the genome. Heterochromatic enrichment for QTL was observed, with approximately 22% of QTL either entirely or partially located in the heterochromatic regions. Heterochromatic gene enrichment was also observed based on their predicted cM locations on the sorghum consensus map, due to suppressed recombination in heterochromatic regions, in contrast to the euchromatic gene enrichment observed on the physical, sequence-based map. The finding of high gene density in recombination-poor regions, coupled with the association with increased QTL density, has implications for the development of more efficient breeding systems in sorghum to better exploit heterosis. The projected QTL information described, combined with the physical locations of sorghum sequence-based markers and predicted gene models, provides sorghum researchers with a useful resource for more detailed analysis of traits and development of efficient marker-assisted breeding strategies.

A case study on the use of legume crop rotations in sugarcane

Growing legume fallow crops has proven to be an important factor in reducing the yield decline effect in sugarcane production. Legumes can also provide a direct economic benefit to sugarcane farmers by providing a source of nitrogen. Further, in some instances, income can flow from the sale, of grain or seed. The following case study provides an insight into the changes made by Russell Young, a sugarcane farmer situated in the Rita Island area of the Burdekin district. The case study focuses on the economics of the old farming system versus a new farming system. The old farming system is based on the conventional farming practices previously used by the Young family in 2002 compared to the 2006 farming system which involves a reduction in tillage practices and use of a Soybean rotational crop for seed production. A whole-of-farm was used to assess the impact of the new farming system on farm profitability. A whole-of-farm economic analysis looks at the impact of a change in farming practice across the whole business, rather than focusing on one single component. This case study is specific to an individual grower’s situation and is not representative of all situations. When evaluating a farming system change, it is important to have a detailed plan.

The role of tillage, fertiliser and forage species in sustaining dairying based on crops in southern Queensland 2. Double-crop and summer sole-crop systems.

Dairy farms located in the subtropical cereal belt of Australia rely on winter and summer cereal crops, rather than pastures, for their forage base. Crops are mostly established in tilled seedbeds and the system is vulnerable to fertility decline and water erosion, particularly over summer fallows. Field studies were conducted over 5 years on contrasting soil types, a Vertosol and Sodosol, in the 650-mm annual-rainfall zone to evaluate the benefits of a modified cropping program on forage productivity and the soil-resource base. Growing forage sorghum as a double-crop with oats increased total mean annual production over that of winter sole-crop systems by 40% and 100% on the Vertosol and Sodosol sites respectively. However, mean annual winter crop yield was halved and overall forage quality was lower. Ninety per cent of the variation in winter crop yield was attributable to fallow and in-crop rainfall. Replacing forage sorghum with the annual legume lablab reduced fertiliser nitrogen (N) requirements and increased forage N concentration, but reduced overall annual yield. Compared with sole-cropped oats, double-cropping reduced the risk of erosion by extending the duration of soil water deficits and increasing the time ground was under plant cover. When grown as a sole-crop, well fertilised forage sorghum achieved a mean annual cumulative yield of 9.64 and 6.05 t DM/ha on the Vertosol and Sodosol, respectively, being about twice that of sole-cropped oats. Forage sorghum established using zero-tillage practices and fertilised at 175 kg N/ha. crop achieved a significantly higher yield and forage N concentration than did the industry-standard forage sorghum (conventional tillage and 55 kg N/ha. crop) on the Vertosol but not on the Sodosol. On the Vertosol, mean annual yield increased from 5.65 to 9.64 t DM/ha (33 kg DM/kg N fertiliser applied above the base rate); the difference in the response between the two sites was attributed to soil type and fertiliser history. Changing both tillage practices and N-fertiliser rate had no affect on fallow water-storage efficiency but did improve fallow ground cover. When forage sorghum, grown as a sole crop, was replaced with lablab in 3 of the 5 years, overall forage N concentration increased significantly, and on the Vertosol, yield and soil nitrate-N reserves also increased significantly relative to industry-standard sorghum. All forage systems maintained or increased the concentration of soil nitrate-N (0-1.2-m soil layer) over the course of the study. Relative to sole-crop oats, alternative forage systems were generally beneficial to the concentration of surface-soil (0-0.1 m) organic carbon and systems that included sorghum showed most promise for increasing soil organic carbon concentration. We conclude that an emphasis on double-or summer sole-cropping rather than winter sole-cropping will advantage both farm productivity and the soil-resource base.

Estimating winter crop area across seasons and regions using time-sequential MODIS imagery.

The wheat grain industry is Australia's second largest agricultural export commodity. There is an increasing demand for accurate, objective and near real-time crop production information by industry. The advent of the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite platform has augmented the capability of satellite-based applications to capture reflectance over large areas at acceptable pixel scale, cost and accuracy. The use of multi-temporal MODIS-enhanced vegetation index (EVI) imagery to determine crop area was investigated in this article. Here the rigour of the harmonic analysis of time-series (HANTS) and early-season metric approaches was assessed when extrapolating over the entire Queensland (QLD) cropping region for the 2005 and 2006 seasons. Early-season crop area estimates, at least 4 months before harvest, produced high accuracy at pixel and regional scales with percent errors of -8.6% and -26% for the 2005 and 2006 seasons, respectively. In discriminating among crops at pixel and regional scale, the HANTS approach showed high accuracy. The errors for specific area estimates for wheat, barley and chickpea were 9.9%, -5.2% and 10.9% (for 2005) and -2.8%, -78% and 64% (for 2006), respectively. Area estimates of total winter crop, wheat, barley and chickpea resulted in coefficient of determination (R(2)) values of 0.92, 0.89, 0.82 and 0.52, when contrasted against the actual shire-scale data. A significantly high coefficient of determination (0.87) was achieved for total winter crop area estimates in August across all shires for the 2006 season. Furthermore, the HANTS approach showed high accuracy in discriminating cropping area from non-cropping area and highlighted the need for accurate and up-to-date land use maps. The extrapolability of these approaches to determine total and specific winter crop area estimates, well before flowering, showed good utility across larger areas and seasons. Hence, it is envisaged that this technology might be transferable to different regions across Australia.

Whole-genome sequencing reveals untapped genetic potential in Africa’s indigenous cereal crop sorghum

Sorghum is a food and feed cereal crop adapted to heat and drought and a staple for 500 million of the world’s poorest people. Its small diploid genome and phenotypic diversity make it an ideal C4 grass model as a complement to C3 rice. Here we present high coverage (16-45 × ) resequenced genomes of 44 sorghum lines representing the primary gene pool and spanning dimensions of geographic origin, end-use and taxonomic group. We also report the first resequenced genome of S. propinquum, identifying 8 M high-quality SNPs, 1.9 M indels and specific gene loss and gain events in S. bicolor. We observe strong racial structure and a complex domestication history involving at least two distinct domestication events. These assembled genomes enable the leveraging of existing cereal functional genomics data against the novel diversity available in sorghum, providing an unmatched resource for the genetic improvement of sorghum and other grass species.