Cover for plans regarding the Naǐbrot, Busul-Montanaǐ, Urchuk, Abuslar i Friling tracts of land in the Fraǐdorf region

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Cover for plans regarding the Rykovo and Lekhkhert N. 50 tracts of landin the Dzhankoĭ region

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Cover for plans regarding theRaitendorf and Maĭfelʻd tracts of land in the Dzhankoĭ region

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Cover for plans regarding the tract of land N 106 in the Dzhankoĭ region

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Cover for plans regarding the Komzetovka - N48, Ikor and Naǐdorf tracts of land in the Evpatoria region

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Allelopathy for weed control in agricultural systems

Weeds are a hidden foe for crop plants, interfering with their functions and suppressing their growth and development. Yield losses of ∼34 are caused by weeds among the major crops, which are grown worldwide. These yield losses are higher than the losses caused by other pests in the crops. Sustainable weed management is needed in the wake of a huge decline in crop outputs due to weed pressure. A diversity in weed management tools ensures sustainable weed control and reduces chances of herbicide resistance development in weeds. Allelopathy as a tool, can be importantly used to combat the challenges of environmental pollution and herbicide resistance development. This review article provides a recent update regarding the practical application of allelopathy for weed control in agricultural systems. Several studies elaborate on the significance of allelopathy for weed management. Rye, sorghum, rice, sunflower, rape seed, and wheat have been documented as important allelopathic crops. These crops express their allelopathic potential by releasing allelochemicals which not only suppress weeds, but also promote underground microbial activities. Crop cultivars with allelopathic potentials can be grown to suppress weeds under field conditions. Further, several types of allelopathic plants can be intercropped with other crops to smother weeds. The use of allelopathic cover crops and mulches can reduce weed pressure in field crops. Rotating a routine crop with an allelopathic crop for one season is another method of allelopathic weed control. Importantly, plant breeding can be explored to improve the allelopathic potential of crop cultivars. In conclusion, allelopathy can be utilized for suppressing weeds in field crops. Allelopathy has a pertinent significance for ecological, sustainable, and integrated weed management systems.

Integrating pest population models with biophysical crop models to better represent the farming system

Farming systems frameworks such as the Agricultural Production Systems simulator (APSIM) represent fluxes through the soil, plant and atmosphere of the system well, but do not generally consider the biotic constraints that function within the system. We designed a method that allowed population models built in DYMEX to interact with APSIM. The simulator engine component of the DYMEX population-modelling platform was wrapped within an APSIM module allowing it to get and set variable values in other APSIM models running in the simulation. A rust model developed in DYMEX is used to demonstrate how the developing rust population reduces the crop's green leaf area. The success of the linking process is seen in the interaction of the two models and how changes in rust population on the crop's leaves feedback to the APSIM crop modifying the growth and development of the crop's leaf area. This linking of population models to simulate pest populations and biophysical models to simulate crop growth and development increases the complexity of the simulation, but provides a tool to investigate biotic constraints within farming systems and further moves APSIM towards being an agro-ecological framework.

Strategic tillage in no-till farming systems in Australia’s northern grains-growing regions: II. Implications for agronomy, soil and environment

In semi-arid sub-tropical areas, a number of studies concerning no-till (NT) farming systems have demonstrated advantages in economic, environmental and soil quality aspects over conventional tillage (CT). However, adoption of continuous NT has contributed to the build-up of herbicide resistant weed populations, increased incidence of soil- and stubble-borne diseases, and stratification of nutrients and organic carbon near the soil surface. Some farmers often resort to an occasional strategic tillage (ST) to manage these problems of NT systems. However, farmers who practice strict NT systems are concerned that even one-time tillage may undo positive soil condition benefits of NT farming systems. We reviewed the pros and cons of the use of occasional ST in NT farming systems. Impacts of occasional ST on agronomy, soil and environment are site-specific and depend on many interacting soil, climatic and management conditions. Most studies conducted in North America and Europe suggest that introducing occasional ST in continuous NT farming systems could improve productivity and profitability in the short term; however in the long-term, the impact is negligible or may be negative. The short term impacts immediately following occasional ST on soil and environment include reduced protective cover, soil loss by erosion, increased runoff, loss of C and water, and reduced microbial activity with little or no detrimental impact in the long-term. A potential negative effect immediately following ST would be reduced plant available water which may result in unreliability of crop sowing in variable seasons. The occurrence of rainfall between the ST and sowing or immediately after the sowing is necessary to replenish soil water lost from the seed zone. Timing of ST is likely to be critical and must be balanced with optimising soil water prior to seeding. The impact of occasional ST varies with the tillage implement used; for example, inversion tillage using mouldboard tillage results in greater impacts as compared to chisel or disc. Opportunities for future research on occasional ST with the most commonly used implements such as tine and/or disc in Australia’s northern grains-growing region are presented in the context of agronomy, soil and the environment.

Assessment of functional forms of crop yield loss models of invasive plant species applied in decision support tools and bioeconomic modelling

AbstractObjectives Decision support tools (DSTs) for invasive species management have had limited success in producing convincing results and meeting users' expectations. The problems could be linked to the functional form of model which represents the dynamic relationship between the invasive species and crop yield loss in the DSTs. The objectives of this study were: a) to compile and review the models tested on field experiments and applied to DSTs; and b) to do an empirical evaluation of some popular models and alternatives. Design and methods This study surveyed the literature and documented strengths and weaknesses of the functional forms of yield loss models. Some widely used models (linear, relative yield and hyperbolic models) and two potentially useful models (the double-scaled and density-scaled models) were evaluated for a wide range of weed densities, maximum potential yield loss and maximum yield loss per weed. Results Popular functional forms include hyperbolic, sigmoid, linear, quadratic and inverse models. Many basic models were modified to account for the effect of important factors (weather, tillage and growth stage of crop at weed emergence) influencing weed–crop interaction and to improve prediction accuracy. This limited their applicability for use in DSTs as they became less generalized in nature and often were applicable to a much narrower range of conditions than would be encountered in the use of DSTs. These factors' effects could be better accounted by using other techniques. Among the model empirically assessed, the linear model is a very simple model which appears to work well at sparse weed densities, but it produces unrealistic behaviour at high densities. The relative-yield model exhibits expected behaviour at high densities and high levels of maximum yield loss per weed but probably underestimates yield loss at low to intermediate densities. The hyperbolic model demonstrated reasonable behaviour at lower weed densities, but produced biologically unreasonable behaviour at low rates of loss per weed and high yield loss at the maximum weed density. The density-scaled model is not sensitive to the yield loss at maximum weed density in terms of the number of weeds that will produce a certain proportion of that maximum yield loss. The double-scaled model appeared to produce more robust estimates of the impact of weeds under a wide range of conditions. Conclusions Previously tested functional forms exhibit problems for use in DSTs for crop yield loss modelling. Of the models evaluated, the double-scaled model exhibits desirable qualitative behaviour under most circumstances.

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.

Crop nutrient application rates

This guide provides information on how to match nutrient rate to crop needs by varying application rates and timing between blocks, guided by soil tests, crop class, cane variety, soil type, block history, soil conditioners and yield expectations.

The growth, reproduction and survival of 'Cascabela thevetia' seedlings under two levels of canopy cover

The ornamental tree 'Cascabela thevetia', from tropical America, has naturalised and formed large infestations at several locations in northern Australia. Some understanding of its ecology and invasiveness was gleaned from a field experiment undertaken in North Queensland. The experiment quantified the growth, time to seed formation and survival of seedlings of the peach biotype growing under light and dense canopy cover within a riparian habitat. Growth, reproduction and survival of young plants varied. Growth was most rapid for seedlings away from, or on the edge of infestations because they were constrained by parent plants. The findings also suggested that land managers have at least 12 months following control to detect new plants, or regrowth, before plants set seed and replenish soil seed banks.

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.

Molecular Breeding for Complex Adaptive Traits: How Integrating Crop Ecophysiology and Modelling Can Enhance Efficiency

Progress in crop improvement is limited by the ability to identify favourable combinations of genotypes (G) and management practices (M) in relevant target environments (E) given the resources available to search among the myriad of possible combinations. To underpin yield advance we require prediction of phenotype based on genotype. In plant breeding, traditional phenotypic selection methods have involved measuring phenotypic performance of large segregating populations in multi-environment trials and applying rigorous statistical procedures based on quantitative genetic theory to identify superior individuals. Recent developments in the ability to inexpensively and densely map/sequence genomes have facilitated a shift from the level of the individual (genotype) to the level of the genomic region. Molecular breeding strategies using genome wide prediction and genomic selection approaches have developed rapidly. However, their applicability to complex traits remains constrained by gene-gene and gene-environment interactions, which restrict the predictive power of associations of genomic regions with phenotypic responses. Here it is argued that crop ecophysiology and functional whole plant modelling can provide an effective link between molecular and organism scales and enhance molecular breeding by adding value to genetic prediction approaches. A physiological framework that facilitates dissection and modelling of complex traits can inform phenotyping methods for marker/gene detection and underpin prediction of likely phenotypic consequences of trait and genetic variation in target environments. This approach holds considerable promise for more effectively linking genotype to phenotype for complex adaptive traits. Specific examples focused on drought adaptation are presented to highlight the concepts.