Legumes or nitrification inhibitors to reduce N2O emissions from subtropical cereal cropping systems in Oxisols?

The DAYCENT biogeochemical model was used to investigate how the use of fertilizers coated with nitrification inhibitors and the introduction of legumes in the crop rotation can affect subtropical cereal production and N2O emissions. The model was validated using comprehensive multi-seasonal, high-frequency dataset from two field investigations conducted on an Oxisol, which is the most common soil type in subtropical regions. Different N fertilizer rates were tested for each N management strategy and simulated under varying weather conditions. DAYCENT was able to reliably predict soil N dynamics, seasonal N2O emissions and crop production, although some discrepancies were observed in the treatments with low or no added N inputs and in the simulation of daily N2O fluxes. Simulations highlighted that the high clay content and the relatively low C levels of the Oxisol analyzed in this study limit the chances for significant amounts of N to be lost via deep leaching or denitrification. The application of urea coated with a nitrification inhibitor was the most effective strategy to minimize N2O emissions. This strategy however did not increase yields since the nitrification inhibitor did not substantially decrease overall N losses compared to conventional urea. Simulations indicated that replacing part of crop N requirements with N mineralized by legume residues is the most effective strategy to reduce N2O emissions and support cereal productivity. The results of this study show that legumes have significant potential to enhance the sustainable and profitable intensification of subtropical cereal cropping systems in Oxisols.

Sugarcane productivity response to different fallow and soybean residue management practices in the Bundaberg district

GRAIN LEGUME ROTATIONS underpin the sustainability of the Australian sugarcane farming system, offering a number of soil health and environmental benefits. Recent studies have highlighted the potential for these breaks to exacerbate nitrous oxide (N2O) emissions. An experiment was implemented in 2012 to evaluate the impact of two fallow management options (bare fallow and soybean break crop) and different soybean residue management practices on N2O emissions and sugarcane productivity. The bare fallow plots were conventionally tilled, whereas the soybean treatments were either tilled, not tilled, residue sprayed with nitrification inhibitor (DMPP) prior to tillage or had a triticale ‘catch crop’ sown between the soybean and sugarcane crops. The fallow plots received either no nitrogen (N0) or fully fertilised (N145) whereas the soybean treatments received 25 kg N/ha at planting only. The Fallow N145 treatment yielded 8% more cane than the soybean tilled treatment. However there was no statistical difference in sugar productivity. Cane yield was correlated with stalk number that was correlated to soil mineral nitrogen status in January. There was only 30% more N/ha in the above-ground biomass between the Fallow N145 and the Fallow N0 treatment; highlighting poor fertiliser nitrogen use efficiency. Supplying adequate nitrogen to meet productivity requirements without causing environmental harm remains a challenge for the Australian sugar industry. The soybean direct drill treatment significantly reduced N2O emissions and produced similar yields and profitability to the soybean tilled treatment (outlined in a companion paper by Wang et.al. in these proceedings). Furthermore, this study has highlighted that the soybean direct drill technique provides an opportunity to enable grain legume cropping in the sugarcane farming system to capture all of the soil health/environmental benefits without exacerbating N2O emissions from Australian sugarcane soils.

Soybean rotation and crop residue management to reduce nitrous oxide emissions from sugarcane soils

NITROUS OXIDE (N2O) IS a potent greenhouse gas and the predominant ozone-depleting substance in the atmosphere. Agricultural nitrogenous fertiliser use is the major source of human-induced N2O emissions. A field experiment was conducted at Bundaberg from October 2012 to September 2014 to examine the impacts of legume crop (soybean) rotation as an alternative nitrogen (N) source on N2O emissions during the fallow period and to investigate low-emission soybean residue management practices. An automatic monitoring system and manual gas sampling chambers were used to measure greenhouse gas emissions from soil. Soybean cropping during the fallow period reduced N2O emissions compared to the bare fallow. Based on the N content in the soybean crop residues, the fertiliser N application rate was reduced by about 120 kg N/ha for the subsequent sugarcane crop. Consequently, emissions of N2O during the sugarcane cropping season were significantly lower from the soybean cropped soil than those from the conventionally fertilised (145 kg N/ha) soil following bare fallow. However, tillage that incorporated the soybean crop residues into soil promoted N2O emissions in the first two months. Spraying a nitrification inhibitor (DMPP) onto the soybean crop residues before tillage effectively prevented the N2O emission spikes. Compared to conventional tillage, practising no-till with or without growing a nitrogen catch crop during the time after soybean harvest and before cane planting also reduced N2O emissions substantially. These results demonstrated that soybean rotation during the fallow period followed with N conservation management practices could offer a promising N2O mitigation strategy in sugarcane farming. Further investigation is required to provide guidance on N and water management following soybean fallow to maintain sugar productivity.

Benzyl isothiocyanate: maximising production in papaya tissue extracts

Abstract: Although mainly grown for its sweet flavoured fruit, papaya (Carica papaya) has also been used for pharmacological purposes for many years. The reasons for use are varied with one of the best known being its anti-fungal action. Benzyl isothiocyanate (BITC) is the constituent most often implicated in this activity. Isothiocyanates are formed when the enzyme myrosinase catalyses the hydrolysis of the non-bioactive glucosinolates. This occurs when cellular contents come into contact through chewing, cutting or during extraction processes in the laboratory. While this is common in Brassica vegetables, the glucosinolate-myrosinase system is rare in fruit, papaya being a notable exception. It contains benzyl glucosinolate (BG), the glucosinolate precursor of BITC, in significant quantities. Parameters that determine the amount of BITC formed are duration of hydrolysis, presence/absence of nitrile-specifier proteins and BG content of different cultivars and tissues. We experimented with differing BITC extraction solvents, with the intention of developing a low cost, natural anti-fungal extract based on under-utilised papaya tissues. The findings suggest that papaya seeds, particularly from quarter-ripe fruit, have the potential to produce the highest levels of BITC necessary. Furthermore, they compare well with the nitrile-specifier protein-containing garden cress seeds (Lepidium sativum). To utilise the papaya seeds as a BITC source, an organic solvent such as ethanol is required to extract the largely water-insoluble BITC from the hydrolysed papaya seed mixture.

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.

Response to deep placed P, K and S in central Queensland

Two field experiments were established in central Queensland at Capella and Gindie to investigate the immediate and then residual benefit of deep placed (20 cm) nutrients in this opportunity cropping system. The field sites had factorial combinations of P (40 kg P/ha), K (200 kg K/ha) and S (40 kg S/ha) and all plots received 100 kg N/ha. No further K or S fertilizers were added during the experiment but some crops had starter P. The Capella site was sown to chickpea in 2012, wheat in 2013 and then chickpea in 2014. The Gindie site was sown to sorghum in 2011/12, chickpea in 2013 and sorghum in early 2015. There were responses to P alone in the first two crops at each site and there were K responses in half the six site years. In year 1 (a good year) both sites showed a 20% grain yield response to only to deep P. In year 2 (much drier) the effects of deep P were still evident at both sites and the effects of K were clearly evident at Gindie. There was a suggestion of an additive P+K effect at Capella and a 50% increase for P+K at Gindie. Year 3 was dry and chickpeas at Capella showed a larger response to P+K but the sorghum at Gindie only responded to deep K. These results indicate that responses to deep placed P and K are durable over an opportunity cropping system, and meeting both requirements is important to achieve yield responses.

A crop productivity research protocol for long wall mining

Springsure Creek Coal (SCC) intends to develop a coal mine using the long wall mining process under grain farming land near Emerald in Central Queensland (CQ). While this technology will result in some subsidence of the land surface, SCC wishes to maintain productivity of the grain cropping land in the precinct after coal mining. However, the impact of the surface subsidence resulting from that mining process on productivity of cropping land in any Australian landscape is currently unclear. A research protocol to investigate the impacts of subsidence on grain productivity for when the SCC project becomes operational is proposed. The protocol has wider application for other similar mining projects throughout the country. A copy of the full report is accessible on www.aginstitute.com.au.

Fertilising for yield and quality in sown grass pastures and forage crops

Sown pasture rundown and declining soil fertility for forage crops are too serious to ignore with losses in beef production of up to 50% across Queensland. The feasibility of using strategic applications of nitrogen (N) fertiliser to address these losses was assessed by analysing a series of scenarios using data drawn from published studies, local fertiliser trials and expert opinion. While N fertilser can dramatically increase productivity (growth, feed quality and beef production gains of over 200% in some scenarios), the estimated economic benefits, derived from paddock level enterprise budgets for a fattening operation, were much more modest. In the best-performing sown grass scenarios, average gross margins were doubled or tripled at the assumed fertiliser response rates, and internal rates of return of up to 11% were achieved. Using fertiliser on forage sorghum or oats was a much less attractive option and, under the paddock level analysis and assumptions used, forages struggled to be profitable even on fertile sites with no fertiliser input. The economics of nitrogen fertilising on grass pasture were sensitive to the assumed response rates in both pasture growth and liveweight gain. Consequently, targeted research is proposed to re-assess the responses used in this analysis, which are largely based on research 25-40 years ago when soils were generally more fertile and pastures less rundown.

Fine root dry matter relative to mango (Mangifera indica) tree scion size grafted on size-controlling rootstocks, is negatively related to scion growth rate

Knowledge of root dry matter (DM) allocation, in relation to differing vigour conferred by rootstock cultivars, is required to understand the structural relationships between rootstock and scion. We investigated the mass of roots (four size classes up to 23 mm diameter) by coring proximal to five polyembryonic mango rootstock cultivars known to differ in their effects on the vigour and productivity of scion cultivar ‘Kensington Pride’, in a field trial of 13-year-old trees. Significant differences in fine (<0.64 and 0.64–1.88 mm diameter) and small (1.88–7.50 mm) root DM contents were observed between rootstock cultivars. There was a complex relationship between the amount of feeder (fine and small size classes) roots and scion size (trunk cross sectional area, TCSA), with intermediate size trees on rootstock MYP having the most feeder roots, while the smallest trees, on the rootstock Vellaikulamban had the least of these roots. Across rootstock cultivars, tree vigour (TCSA growth rate) was negatively and significantly related to the ratio of fine root DM/scion TCSA, suggesting this may be a useful indicator of the vigour that different rootstocks confer on the scion. In contrast non-ratio root DM and scion TCSA results had no significant relationships. The significant rootstock effects on orchard root growth and tree size could not be predicted from earlier differences in nursery seedling vigour, nor did seedling vigour predict root DM allocation.

Automating Crop Damage Assessments with Unmanned Aerial Systems and Machine Learning

Agricultural pests are responsible for millions of dollars in crop losses and management costs every year. In order to implement optimal site-specific treatments and reduce control costs, new methods to accurately monitor and assess pest damage need to be investigated. In this paper we explore the combination of unmanned aerial vehicles (UAV), remote sensing and machine learning techniques as a promising methodology to address this challenge. The deployment of UAVs as a sensor platform is a rapidly growing field of study for biosecurity and precision agriculture applications. In this experiment, a data collection campaign is performed over a sorghum crop severely damaged by white grubs (Coleoptera: Scarabaeidae). The larvae of these scarab beetles feed on the roots of plants, which in turn impairs root exploration of the soil profile. In the field, crop health status could be classified according to three levels: bare soil where plants were decimated, transition zones of reduced plant density and healthy canopy areas. In this study, we describe the UAV platform deployed to collect high-resolution RGB imagery as well as the image processing pipeline implemented to create an orthoimage. An unsupervised machine learning approach is formulated in order to create a meaningful partition of the image into each of the crop levels. The aim of this approach is to simplify the image analysis step by minimizing user input requirements and avoiding the manual data labelling necessary in supervised learning approaches. The implemented algorithm is based on the K-means clustering algorithm. In order to control high-frequency components present in the feature space, a neighbourhood-oriented parameter is introduced by applying Gaussian convolution kernels prior to K-means clustering. The results show the algorithm delivers consistent decision boundaries that classify the field into three clusters, one for each crop health level as shown in Figure 1. The methodology presented in this paper represents a venue for further esearch towards automated crop damage assessments and biosecurity surveillance.