Academic literature on the topic 'Peanuts South Australia; Peanut industry'

Abstract In most years, peanuts from the south-central US have excellent soluble sugar levels for the food industry; however, in some growing seasons high sugar contents are a significant problem associated with roasted color variation. To test the hypothesis that high sugar concentration was related to low temperature extremes, this study evaluated temperature effects on carbohydrate levels in peanuts grown hydroponically. Peanuts were grown with separate pod-zone and shoot-root zone day/night temperatures. Peanut carbohydrate contents were evaluated in seed from pods grown at nighttime pod-zone temperatures of 15, 20, 22, 24 and 28 C. Total carbohydrates were higher in peanuts grown in 15 C pod-zone temperatures compared with those maintained at 28 C. Peanuts harvested at 120 d after planting (DAP) had the highest sucrose contents at 15 and 20 C, the second highest sucrose contents at 22 C, and the lowest sucrose concentration at 24 C. The temperature-induced differential in sucrose contents of 120 DAP peanuts was not observed in peanuts harvested at 141 DAP. These findings support the observation that soil temperature has a greater impact on peanut carbohydrate accumulation than air temperature. The results also suggest that nighttime soil temperatures of 15 C will result in more mature peanuts if they are grown for 141 d after planting; however, harvesting before the peanuts reach maturity may result in elevated sugar contents.

Sclerotinia Blight, caused by ascomycete fungal pathogen S. minor (Jagger), is a serious soil-borne disease of peanut crops within the South Burnett area in Queensland, Australia. The pathogen can infect root, stem and foliage tissues, forming characteristic fluffy white mycelial growth on stems leading to tissue wilting and necrosis. The disease can cause significant yield reductions and, in some cases, complete crop losses in peanut production. Outbreaks occur in cooler weather (under 18 °C) with high humidity levels (above 95%) as the higher humidity levels promote germination of sclerotia (Smith 2003, Maas, Dashiell et al. 2006). Therefore, knowledge of inoculum levels prior to sowing could enhance cropping systems through enhanced capacity to predict outbreaks. The South Australia Research and Development Institute (SARDI) offers a new soil test for Sclerotinia sp., called PreDictaB, available for farmers to asses inoculum levels pre-planting as a crop risk assessment tool. This project validated the accuracy of the PreDictaB test for Sclerotinia inoculum levels in the South Burnett soils, while gathering paddock and weather data to identify key characteristics linked to high risk of Sclerotinia Blight incidence to be transposed in a pre-season risk matrix model. Results demonstrated a close positive relationship between the level of Sclerotinia in the soil pre-planting and the paddock disease severity observed at harvest. The significance of the results for future research into potential management strategies is discussed. This new test has the potential to reduce the impact and presence of Sclerotinia in the field within the South Burnett region.

The peanut (Arachys hypogaea) is a plant of the Fabaceae family (legumes), as are chickpeas, lentils, beans, and peas. It is originally from South America and is used mainly for culinary purposes, in confectionery products, or as a nut as well as for the production of biscuits, breads, sweets, cereals, and salads. Also, due to its high percentage of fat, peanuts are used for industrialized products such as oils, flours, inks, creams, lipsticks, etc. According to the Food and Agriculture Organization (FAO) statistical yearbook in 2016, the production of peanuts was 43,982,066 t, produced in 27,660,802 hectares. Peanuts are grown mainly in Asia, with a global production rate of 65.3%, followed by Africa with 26.2%, the Americas with 8.4%, and Oceania with 0.1%. The peanut industry is one of the main generators of agroindustrial waste (shells). This residual biomass (25–30% of the total weight) has a high energy content that is worth exploring. The main objectives of this study are, firstly, to evaluate the energy parameters of peanut shells as a possible solid biofuel applied as an energy source in residential and industrial heating installations. Secondly, different models are analysed to estimate the higher heating value (HHV) for biomass proposed by different scientists and to determine which most accurately fits the determination of this value for peanut shells. Thirdly, we evaluate the reduction in global CO2 emissions that would result from the use of peanut shells as biofuel. The obtained HHV of peanut shells (18.547 MJ/kg) is higher than other biomass sources evaluated, such as olive stones (17.884 MJ/kg) or almond shells (18.200 MJ/kg), and similar to other sources of biomass used at present for home and industrial heating applications. Different prediction models of the HHV value proposed by scientists for different types of biomass have been analysed and the one that best fits the calculation for the peanut shell has been determined. The CO2 reduction that would result from the use of peanut shells as an energy source has been evaluated in all production countries, obtaining values above 0.5 ‰ of their total emissions.

With the aim of increasing peanut production in Australia, the Australian peanut industry has recently considered growing peanuts in rotation with maize at Katherine in the Northern Territory—a location with a semi-arid tropical climate and surplus irrigation capacity. We used the well-validated APSIM model to examine potential agronomic benefits and long-term risks of this strategy under the current and warmer climates of the new region. Yield of the two crops, irrigation requirement, total soil organic carbon (SOC), nitrogen (N) losses and greenhouse gas (GHG) emissions were simulated. Sixteen climate stressors were used; these were generated by using global climate models ECHAM5, GFDL2.1, GFDL2.0 and MRIGCM232 with a median sensitivity under two Special Report of Emissions Scenarios over the 2030 and 2050 timeframes plus current climate (baseline) for Katherine. Effects were compared at three levels of irrigation and three levels of N fertiliser applied to maize grown in rotations of wet-season peanut and dry-season maize (WPDM), and wet-season maize and dry-season peanut (WMDP). The climate stressors projected average temperature increases of 1°C to 2.8°C in the dry (baseline 24.4°C) and wet (baseline 29.5°C) seasons for the 2030 and 2050 timeframes, respectively. Increased temperature caused a reduction in yield of both crops in both rotations. However, the overall yield advantage of WPDM increased from 41% to up to 53% compared with the industry-preferred sequence of WMDP under the worst climate projection. Increased temperature increased the irrigation requirement by up to 11% in WPDM, but caused a smaller reduction in total SOC accumulation and smaller increases in N losses and GHG emission compared with WMDP. We conclude that although increased temperature will reduce productivity and total SOC accumulation, and increase N losses and GHG emissions in Katherine or similar northern Australian environments, the WPDM sequence should be preferable over the industry-preferred sequence because of its overall yield and sustainability advantages in warmer climates. Any limitations of irrigation resulting from climate change could, however, limit these advantages.

Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing o/Southern bodies the industtry could profitable to adjust their operations stategically. Significantly , physically based lag-relationships exist between an index of ocean/atmospher EI Niño/southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.

AbstractLarge larval populations of the scarabaeid beetle Heteronyx piceus Blanchard that occur under peanuts, but not maize, in the South Burnett region of Australia are the result of a high rate and prolonged period of egg production by females feeding on peanut foliage. Heteronyx piceus is a relatively sedentary species and movement of females between adjacent fields is low. Populations of H. piceus varied markedly with landscape position. High larval populations are more likely (1 in 4 chance) to be encountered on the ‘scrub’ soils in the upper parts of the landscape than in the ‘forest’ soils in the lower half (1 in 20 chance), indicating that soil type/landscape position is a key risk factor in assessing the need for management intervention. The studies indicate that, because of the species' sedentary nature, the most meaningful population entity for management of H. piceus is the individual field, rather than the whole-farm or the region. The implications of this population ecology for management of the pest are discussed in relation to control strategies.

Flocks of brolgas (Antigone rubicunda) and Australian sarus cranes (A. antigone gillae) congregate in cropping areas of the Atherton Tablelands in north Queensland, Australia, during the non-breeding months of May to December each year and sometimes come into conflict with farmers. The central part of the region has been declared a Key Biodiversity Area, largely because it is the only well known non-breeding area for the Australian sarus crane. We investigated spatial and temporal patterns of use of this landscape for foraging by the two species to determine how they might be affected by changes in cropping. Abundances of the species were positively correlated with each other over both time and space. Sarus cranes were nevertheless markedly more abundant on the fertile volcanic soils of the central Tablelands, whilst brolgas were more abundant on a variety of soils in outlying cropping areas close to roost sites, especially in the south-west of the region. Both species used a wide variety of crops and pastures but occurred at highest densities on ploughed land and areas from which crops (especially maize) had been harvested. In addition, brolgas were also strongly associated with early-stage winter cereals with volunteer peanuts from the previous crop. We conclude that maize and peanut crops are important as foraging sites for both species during the non-breeding season, a situation that requires management in the interest of both cranes and farmers, especially as cropping patterns intensify and agricultural technology changes. However, we also note that flocking on the Atherton Tablelands indicates that brolgas and sarus cranes are likely to be adaptable to change and able to take advantage of newly created cropping areas.

Bibliography: leaves 189-202
209 leaves : ill. (some col.), maps ; 30 cm.
The object of this thesis was to obtain information relevant to the development of peanut production in southern Australia... The results showed the importance of spatial arrangement and plant density when trying to optimise yield potential.
Thesis (Ph.D.) -- University of Adelaide, Dept. of Agronomy and Farming Systems, 2000