Near infrared reflectance as a rapid and inexpensive surrogate measure for fatty acid composition and oil content in peanuts (Arachis hypogaea L.)

The fatty acid composition of ground nuts (Arachis hypogaea L.) commonly known as peanuts, is an important consideration when a new variety is being released. The composition impacts on nutrition and, importantly, self-life of peanut products. To select for suitable breeding material, it was necessary to develop a rapid, non-derstructive and cost-efficient method. Near infrared spectroscopy was chosen as that methodology. Calibrations were developed for two major fatty-acid components, oleic and linoleic acids and two minor components, palmitic and stearic acids, as well as total oil content. Partial least squares models indicated a high level of precision with a squared multiple correlation coefficient of greater than 0.90 for each constitutent. Standard errors for prediction for oleic, linoleic, palmitic, stearic acids and total oil content were 6.4%, 4.5%, 0.8%, 0.9% and 1.3% respectively. The results demonstrated that reasonable calibrations could be developed to predict oil composition and content of peanuts for a breeding programme.

Application of a model to assess aflatoxin risk in peanuts.

When exposed to hot (22-35 degrees C) and dry climatic conditions in the field during the final 4-6 weeks of pod filling, peanuts (Arachis hypogaea L.) can accumulate highly carcinogenic and immuno-suppressing aflatoxins. Forecasting of the risk posed by these conditions can assist in minimizing pre-harvest contamination. A model was therefore developed as part of the Agricultural Production Systems Simulator (APSIM) peanut module, which calculated an aflatoxin risk index (ARI) using four temperature response functions when fractional available soil water was <0.20 and the crop was in the last 0.40 of the pod-filling phase. ARI explained 0.95 (P <= 0.05) of the variation in aflatoxin contamination, which varied from 0 to c. 800 mu g/kg in 17 large-scale sowings in tropical and four sowings in sub-tropical environments carried out in Australia between 13 November and 16 December 2007. ARI also explained 0.96 (P <= 0.01) of the variation in the proportion of aflatoxin-contaminated loads (>15 mu g/kg) of peanuts in the Kingaroy region of Australia during the period between the 1998/99 and 2007/08 seasons. Simulation of ARI using historical climatic data from 1890 to 2007 indicated a three-fold increase in its value since 1980 compared to the entire previous period. The increase was associated with increases in ambient temperature and decreases in rainfall. To facilitate routine monitoring of aflatoxin risk by growers in near real time, a web interface of the model was also developed. The ARI predicted using this interface for eight growers correlated significantly with the level of contamination in crops (r=095, P <= 0.01). These results suggest that ARI simulated by the model is a reliable indicator of aflatoxin contamination that can be used in aflatoxin research as well as a decision-support tool to monitor pre-harvest aflatoxin risk in peanuts.

AQUAMAN: a web-based decision support system for irrigation scheduling in peanuts

Peanut (Arachis hypogaea L.) is an economically important legume crop in irrigated production areas of northern Australia. Although the potential pod yield of the crop in these areas is about 8 t ha(-1), most growers generally obtain around 5 t ha(-1), partly due to poor irrigation management. Better information and tools that are easy to use, accurate, and cost-effective are therefore needed to help local peanut growers improve irrigation management. This paper introduces a new web-based decision support system called AQUAMAN that was developed to assist Australian peanut growers schedule irrigations. It simulates the timing and depth of future irrigations by combining procedures from the food and agriculture organization (FAO) guidelines for irrigation scheduling (FAO-56) with those of the agricultural production systems simulator (APSIM) modeling framework. Here, we present a description of AQUAMAN and results of a series of activities (i.e., extension activities, case studies, and a survey) that were conducted to assess its level of acceptance among Australian peanut growers, obtain feedback for future improvements, and evaluate its performance. Application of the tool for scheduling irrigations of commercial peanut farms since its release in 2004-2005 has shown good acceptance by local peanuts growers and potential for significantly improving yield. Limited comparison with the farmer practice of matching the pan evaporation demand during rain-free periods in 2006-2007 and 2008-2009 suggested that AQUAMAN enabled irrigation water savings of up to 50% and the realization of enhanced water and irrigation use efficiencies.

Analysis of Crude Protein and Allergen Abundance in Peanuts (Arachis hypogaea cv. Walter) from Three Growing Regions in Australia

The effects of plant growth conditions on concentrations of proteins, including allergens, in peanut (Arachis hypogaea L.) kernels are largely unknown. Peanuts (cv. Walter) were grown at five sites (Taabinga, Redvale, Childers, Bundaberg, and Kairi) covering three commercial growing regions in Queensland, Australia. Differences in temperature, rainfall, and solar radiation during the growing season were evaluated. Kernel yield varied from 2.3 t/ha (Kairi) to 3.9 t/ha (Childers), probably due to differences in solar radiation. Crude protein appeared to vary only between Kairi and Childers, whereas Ara h 1 and 2 concentrations were similar in all locations. 2D-DIGE revealed significant differences in spot volumes for only two minor protein spots from peanuts grown in the five locations. Western blotting using peanut-allergic serum revealed no qualitative differences in recognition of antigens. It was concluded that peanuts grown in different growing regions in Queensland, Australia, had similar protein compositions and therefore were unlikely to show differences in allergenicity.

Population ecology of Heteronyx piceus (Coleoptera: Scarabaeidae) in a peanut/maize cropping system

Large 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.

Modelling climatic risks of aflatoxin contamination in maize

Aflatoxins are highly carcinogenic mycotoxins produced by two fungi, Aspergillus flavus and A. parasiticus, under specific moisture and temperature conditions before harvest and/or during storage of a wide range of crops including maize. Modelling of interactions between host plant and environment during the season can enable quantification of preharvest aflatoxin risk and its potential management. A model was developed to quantify climatic risks of aflatoxin contamination in maize using principles previously used for peanuts. The model outputs an aflatoxin risk index in response to seasonal temperature and soil moisture during the maize grain filling period using the APSIM's maize module. The model performed well in simulating climatic risk of aflatoxin contamination in maize as indicated by a significant R2 (P ≤ 0.01) between aflatoxin risk index and the measured aflatoxin B1 in crop samples, which was 0.69 for a range of rainfed Australian locations and 0.62 when irrigated locations were also included in the analysis. The model was further applied to determine probabilities of exceeding a given aflatoxin risk in four non-irrigated maize growing locations of Queensland using 106 years of historical climatic data. Locations with both dry and hot climates had a much higher probability of higher aflatoxin risk compared with locations having either dry or hot conditions alone. Scenario analysis suggested that under non-irrigated conditions the risk of aflatoxin contamination could be minimised by adjusting sowing time or selecting an appropriate hybrid to better match the grain filling period to coincide with lower temperature and water stress conditions.

Using APSIM-soiltemp to simulate soil temperature in the podding zone of peanut

Measurement or accurate simulation of soil temperature is important for improved understanding and management of peanuts (Arachis hypogaea L.), due to their geocarpic habit. A module of the Agricultural Production Systems Simulator Model (APSIM), APSIM-soiltemp, which uses input of ambient temperature, rainfall and solar radiation in conjunction with other APSIM modules, was evaluated for its ability to simulate surface 5 cm soil temperature in 35 peanut on-farm trials conducted between 2001 and 2005 in the Burnett region (25°36'S to 26°41'S, 151°39'E to 151°53'E). Soil temperature simulated by the APSIM-soiltemp module, from 30 days after sowing until maturity, closely matched the measured values (R2 ≥ 0.80)in the first three seasons (2001-04). However, a slightly poorer relationship (R2 = 0.55) between the observed and the simulated temperatures was observed in 2004-05, when the crop was severely water stressed. Nevertheless, over all the four seasons, which were characterised by a range of ambient temperature, leaf area index, radiation and soil water, each of which was found to have significant effects on soil temperature, a close 1:1 relationship (R2 = 0.85) between measured and simulated soil temperatures was observed. Therefore, the pod zone soil temperature simulated by the module can be generally relied on in place of measured input of soil temperature in APSIM applications, such as quantifying climatic risk of aflatoxin accumulation.

Runoff, soil loss, and nutrient transport from cropping systems on Red Ferrosols in tropical northern Australia.

Runoff, soil loss, and nutrient loss were assessed on a Red Ferrosol in tropical Australia over 3 years. The experiment was conducted using bounded, 100-m(2) field plots cropped to peanuts, maize, or grass. A bare plot, without cover or crop, was also instigated as an extreme treatment. Results showed the importance of cover in reducing runoff, soil loss, and nutrient loss from these soils. Runoff ranged from 13% of incident rainfall for the conventional cultivation to 29% under bare conditions during the highest rainfall year, and was well correlated with event rainfall and rainfall energy. Soil loss ranged from 30 t/ha. year under bare conditions to <6 t/ha. year under cropping. Nutrient losses of 35 kg N and 35 kg P/ha. year under bare conditions and 17 kg N and 11 kg P/ha. year under cropping were measured. Soil carbon analyses showed a relationship with treatment runoff, suggesting that soil properties influenced the rainfall runoff response. The cropping systems model PERFECT was calibrated using runoff, soil loss, and soil water data. Runoff and soil loss showed good agreement with observed data in the calibration, and soil water and yield had reasonable agreement. Longterm runs using historical weather data showed the episodic nature of runoff and soil loss events in this region and emphasise the need to manage land using protective measures such as conservation cropping practices. Farmers involved in related, action-learning activities wished to incorporate conservation cropping findings into their systems but also needed clear production benefits to hasten practice change.

DAQ00129 Improving the Integration of Legumes in Grain and Sugarcane Farming Systems in Southern Queensland

The farming systems and agribusinesses of the inland Burnett and southern coastal cropping regions of Queensland are becoming increasingly interlinked as grain legume crops, a key component of dryland cropping systems, become more firmly entrenched in the coastal sugarcane cropping areas. Soybeans, peanuts and possibly winter cereals like barley have a real and demonstrated role in sugarcane rotations, and assistance with the integration of those crops into viable and sustainable cropping systems with sugarcane will be critical to the futuer development of these industries.

ACIAR Productivity and profitability enhancing tropical pulses in Indonesia and Australia

The project aims at improving the productivity and profitability of mung beans, soy beans and peanuts.

Productivity and marketing enhancement for peanut in Papua New Guinea and Australia

Enhance productivity of peanuts in Papua New Guinea and Australia. Also the application of remote sensing technologies to enhance profitability in peanut systems.

Agronomic benefits and risks associated with the irrigated peanut–maize production system under a changing climate in northern Australia

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.