Optimal simultaneous maximum a posterioriestimation of states, noise statistics and parameters I. Algorithm

The simultaneous state and parameter estimation problem for a linear discrete-time system with unknown noise statistics is treated as a large-scale optimization problem. The a posterioriprobability density function is maximized directly with respect to the states and parameters subject to the constraint of the system dynamics. The resulting optimization problem is too large for any of the standard non-linear programming techniques and hence an hierarchical optimization approach is proposed. It turns out that the states can be computed at the first levelfor given noise and system parameters. These, in turn, are to be modified at the second level.The states are to be computed from a large system of linear equations and two solution methods are considered for solving these equations, limiting the horizon to a suitable length. The resulting algorithm is a filter-smoother, suitable for off-line as well as on-line state estimation for given noise and system parameters. The second level problem is split up into two, one for modifying the noise statistics and the other for modifying the system parameters. An adaptive relaxation technique is proposed for modifying the noise statistics and a modified Gauss-Newton technique is used to adjust the system parameters.

Optimal simultaneous maximum a posterioriestimation of states, noise statistics and parameters II. Numerical performance

A very general and numerically quite robust algorithm has been proposed by Sastry and Gauvrit (1980) for system identification. The present paper takes it up and examines its performance on a real test example. The example considered is the lateral dynamics of an aircraft. This is used as a vehicle for demonstrating the performance of various aspects of the algorithm in several possible modes.

Agronomic challenges for organic crop husbandry

With respect to resource management and environmental impact, organic farming offers rationales for agricultural sustainability. However, agronomic productivity is usually higher with conventional farming. This work aimed at investigating two factors of major importance for the agronomic productivity of organic crop husbandry, nitrogen (N) supply through symbiotic N fixation (SNF) and weed occurrence. Perennial red clover-grass leys and spring cereal crops subjected to regular agricultural practices were studied on 34 organic farms located in the southern and the north-western coastal regions of Finland. Herbage growth, clover content as a proportion of the ley and extent of SNF in perennial leys, and the occurrence of weed species and weed-crop competition in spring cereal stands were related to climate conditions, soil properties, and management measures. The herbage accumulated from the first and the second cut of one- and two-year-old leys averaged 7.5 t DM ha-1 (SD ± 1.7 t DM ha-1); the clover content averaged 43.9% (SD ± 18.8%). Along with the clover content, herbage production decreased with ley age. Radiation use efficiency (RUE) correlated positively with clover proportion but despite low clover contents, three-year-old leys were still productive with regard to RUE. SNF in the accumulated annual growth of one- and two-year-old leys averaged 247.5 kg N ha-1 yr-1 (SD ± 114.4 kg N ha-1 yr-1). It was supposed that if red clover-grass leys constituted 40% of the rotation, then the mean N supply by SNF would be able to sustain two or three succeeding cereal crops (green manure and forage ley, respectively), yielding 3.0 to 4.0 t grain ha-1. Being a function of clover biomass, the SNF increased from the first to the second cut and thereafter declined with ley age. Coefficients of variation of clover contents (and SNF) between and within fields were around 50%, which was about twice as high as those of herbage production. The lower were the clover contents, the higher were the within-field variations of clover as a proportion of the ley. Low clover contents in one-year-old leys and increasing variability with ley age suggested that red clover growth was limited by poor establishment and poor overwintering. The proportions of clover in leys were lower and their variability was higher in the northwest than in the south. Soil properties, primarily texture and structure, had a major impact on clover proportion and herbage production, which largely explained regional differences in ley growth. Within-field variability of soil properties can be amended through site-specific measures, including drainage, liming, and applications of organic manures and mineral fertilizers. Overwintering and the persistence of leys can be improved by the choice of winter-hardy varieties, careful establishment and the appropriate harvest regime. Mean grain yields of spring cereal crops amounted to 3.2 t ha-1 in the south and 3.6 t ha-1 in the northwest. At 570 and 565 m-2 for the south and northwest respectively, mean weed densities did not differ between the regions, whereas the respective mean weed biomass of 697 and 1594 kg dry weight ha-1, respectively did differ. Weed abundance varied remarkably between single fields. The number of weed species was higher in the south than in the northwest. For example, Fumaria officinalis and Lamium spp. were found only in the south. Frequencies and abundances of Lapsana communis, Myosotis arvensis, Polygonum aviculare, Tripleurospermum inodorum, and Vicia spp. were higher in the south, whereas those of Elymus repens, Persicaria spp. and Spergula arvensis were higher in the northwest. The number of years since conversion to organic farming, i.e. long-term management, was one of the variables that explained the abundance of single weed species. E. repens was the weed species whose biomass increased most with the duration of organic farming. Another significant variable was crop biomass, which was affected by short-term management. The presence of different weed species was related to the duration of organic farming and to low crop yield. This finding demonstrated that it was not the organic farming regime per se, which resulted in high weed infestation and low yielding crops, but failures in the understanding and the management of organic farming systems. Successful weed control relies on farm- and field-specific long- and short-term management approaches. The agronomic productivity of ley and spring cereal crops managed by full-time farmers with an interest in organic farming was on the same level as of the mean for conventional farming. Given the many options for further improvements of the agronomic performance of organic arable systems, organic farming offers foundations for the development of sustainable agriculture. The main threat to the sustainability of farming in Finland, both conventional and organic, is the spatial separation of crop production and animal husbandry by region, along with the simplification of associated crop rotations.

Stunted cotton (Gossypium hirsutum L.) fully recovers biomass and yield of seed cotton after delayed root inoculation with spores of an arbuscular mycorrhizal fungus (Glomus mosseae)

In the northern grain and cotton region of Australia, poor crop growth after long periods of fallow, called 'long-fallow' disorder, is caused by a decline of natural arbuscular-mycorrhizal fungi (AMF). When cotton was grown in large pots containing 22 kg of Vertisol from a field recently harvested from cotton in Central Queensland, plants in pasteurised soil were extremely stunted compared with plants in unpasteurised soil. We tested the hypothesis that this extreme stunting was caused by the absence of AMF and examined whether such stunted plants could recover from subsequent treatment with AMF spores and/or P fertiliser. At 42 days after sowing, the healthy cotton growing in unpasteurised soil had 48% of its root-length colonised with AMF, whereas the stunted cotton had none. After inoculation with AMF spores (6 spores/g soil of Glomus mosseae) and/or application of P fertiliser (50 mg P/kg soil) at 45 days after sowing, the stunted plants commenced to improve about 25 days after treatment, and continued until their total dry matter and seed cotton production equalled that of plants growing in unpasteurised soil with natural AMF. In contrast, non-mycorrhizal cotton grown without P fertiliser remained stunted throughout and produced no bolls and only 1% of the biomass of mycorrhizal cotton. Even with the addition of P fertiliser, non-mycorrhizal cotton produced only 64% of the biomass and 58% of the seed cotton (lint + seed) of mycorrhizal cotton plants. These results show that cotton is highly dependent on AMF for P nutrition and growth in Vertisol (even with high rates of P fertiliser), but can recover from complete lack of AMF and consequent stunting during at least the first 45 days of growth when treated with AMF spores and/or P fertiliser. This corroborates field observations in the northern region that cotton may recover from long-fallow disorder caused by low initial levels of AMF propagules in the soil as the AMF colonisation of its roots increases during the growing season.

Undersowing in a northern climate: effects on spring cereal yield and risk of nitrate leaching

Disadvantages of invariable cereal cropping, concern of nutrient leaching and prices of nitrogen (N) fertilizer have all increased during last decades. An undersown crop, which grows together with a main crop and after harvest, could mitigate all those questions. The aim of this study was to develop undersowing in Finnish conditions, so that it suits for spring cereal farming as well as possible and enhances taking care of soil and environment, especially when control of N is concerned. In total, 17 plant species were undersown in spring cereals during the field experiments between 1991-1999 at four sites in South and Central Finland, but after selection, eight of them were studied more thoroughly. Two legumes, one grass species and one mixture of them were included in long-term trials in order to study annually repeated undersowing. Further, simultaneous broadcasting of seeds instead of separate undersowing was studied. Grain yield response and the capacity of the undersown crop to absorb soil N or fix N from atmosphere, and the release of N were of greatest interest. Seeding rates of undersown crops and N fertilization rates during annually repeated undersowing were also studied. Italian ryegrass (Lolium multiflorum Lam., IR) absorbed soil nitrate N (NO3-N) most efficiently in autumn and timothy (Phleum pratense L.) in spring. The capacity of other grass species to absorb N was low, or it was insufficient considering the negative effect on grain yield. Red clover (Trifolium pratense L.) and white clover (Trifolium repens L.) suited well in annually repeated undersowing, supplying fixed N for cereals without markedly increased risk of N leaching. Autumn oriented growth rhythm of the studied legumes was optimal for undersowing, whereas the growth rhythm of grasses was less suited but varied between species. A model of adaptive undersowing system was outlined in order to emphasize allocation of measures according needs. After defining the goal of undersowing, many decisions are to be done. When diminishing N leaching is primarily sought, a mixture of IR and timothy is advantageous. Clovers suit for replacing N fertilization, as the positive residual effect is greater than the negative effect caused by competition. A mixture of legume and non legume is a good choice when increased diversity is the main target. Seeding rate is an efficient means for adjusting competition and N effects. Broadcasting with soil covering equipment can be used to establish an undersown crop. In addition, timing and method of cover crop termination have an important role in the outcome. Continuous observing of the system is needed as for instance conditions significantly affect growth of undersown crop and on the other hand N release from crop residues may increase in long run.

Association genetics in Corymbia citriodora subsp variegata identifies single nucleotide polymorphisms affecting wood growth and cellulosic pulp yield

Wood is an important biological resource which contributes to nutrient and hydrology cycles through ecosystems, and provides structural support at the plant level. Thousands of genes are involved in wood development, yet their effects on phenotype are not well understood. We have exploited the low genomic linkage disequilibrium (LD) and abundant phenotypic variation of forest trees to explore allelic diversity underlying wood traits in an association study. Candidate gene allelic diversity was modelled against quantitative variation to identify SNPs influencing wood properties, growth and disease resistance across three populations of Corymbia citriodora subsp. variegata, a forest tree of eastern Australia. Nine single nucleotide polymorphism (SNP) associations from six genes were identified in a discovery population (833 individuals). Associations were subsequently tested in two smaller populations (130160 individuals), validating our findings in three cases for actin 7 (ACT7) and COP1 interacting protein 7 (CIP7). The results imply a functional role for these genes in mediating wood chemical composition and growth, respectively. A flip in the effect of ACT7 on pulp yield between populations suggests gene by environment interactions are at play. Existing evidence of gene function lends strength to the observed associations, and in the case of CIP7 supports a role in cortical photosynthesis.

Microbial indicators related to yield and disease and changes in soil microbial community structure with ginger farm management practices

TRFLP (terminal restriction fragment length polymorphism) was used to assess whether management practices that improved disease suppression and/or yield in a 4-year ginger field trial were related to changes in soil microbial community structure. Bacterial and fungal community profiles were defined by presence and abundance of terminal restriction fragments (TRFs), where each TRF represents one or more species. Results indicated inclusion of an organic amendment and minimum tillage increased the relative diversity of dominant fungal populations in a system dependant way. Inclusion of an organic amendment increased bacterial species richness in the pasture treatment. Redundancy analysis showed shifts in microbial community structure associated with different management practices and treatments grouped according to TRF abundance in relation to yield and disease incidence. ANOVA also indicated the abundance of certain TRFs was significantly affected by farming system management practices, and a number of these TRFs were also correlated with yield or disease suppression. Further analyses are required to determine whether identified TRFs can be used as general or soil-type specific bio-indicators of productivity (increased and decreased) and Pythium myriotylum suppressiveness.

Sustainable management for rangelands in a variable climate: evidence and insights from northern Australia

Inter-annual rainfall variability is a major challenge to sustainable and productive grazing management on rangelands. In Australia, rainfall variability is particularly pronounced and failure to manage appropriately leads to major economic loss and environmental degradation. Recommended strategies to manage sustainably include stocking at long-term carrying capacity (LTCC) or varying stock numbers with forage availability. These strategies are conceptually simple but difficult to implement, given the scale and spatial heterogeneity of grazing properties and the uncertainty of the climate. This paper presents learnings and insights from northern Australia gained from research and modelling on managing for rainfall variability. A method to objectively estimate LTCC in large, heterogeneous paddocks is discussed, and guidelines and tools to tactically adjust stocking rates are presented. The possible use of seasonal climate forecasts (SCF) in management is also considered. Results from a 13-year grazing trial in Queensland show that constant stocking at LTCC was far more profitable and largely maintained land condition compared with heavy stocking (HSR). Variable stocking (VAR) with or without the use of SCF was marginally more profitable, but income variability was greater and land condition poorer than constant stocking at LTCC. Two commercial scale trials in the Northern Territory with breeder cows highlighted the practical difficulties of variable stocking and provided evidence that heavier pasture utilisation rates depress reproductive performance. Simulation modelling across a range of regions in northern Australia also showed a decline in resource condition and profitability under heavy stocking rates. Modelling further suggested that the relative value of variable v. constant stocking depends on stocking rate and land condition. Importantly, variable stocking may possibly allow slightly higher stocking rates without pasture degradation. Enterprise-level simulations run for breeder herds nevertheless show that poor economic performance can occur under constant stocking and even under variable stocking in some circumstances. Modelling and research results both suggest that a form of constrained flexible stocking should be applied to manage for climate variability. Active adaptive management and research will be required as future climate changes make managing for rainfall variability increasingly challenging.

Stochastic model for simulating maize yield

Maize is one of the most important crops in the world. The products generated from this crop are largely used in the starch industry, the animal and human nutrition sector, and biomass energy production and refineries. For these reasons, there is much interest in figuring the potential grain yield of maize genotypes in relation to the environment in which they will be grown, as the productivity directly affects agribusiness or farm profitability. Questions like these can be investigated with ecophysiological crop models, which can be organized according to different philosophies and structures. The main objective of this work is to conceptualize a stochastic model for predicting maize grain yield and productivity under different conditions of water supply while considering the uncertainties of daily climate data. Therefore, one focus is to explain the model construction in detail, and the other is to present some results in light of the philosophy adopted. A deterministic model was built as the basis for the stochastic model. The former performed well in terms of the curve shape of the above-ground dry matter over time as well as the grain yield under full and moderate water deficit conditions. Through the use of a triangular distribution for the harvest index and a bivariate normal distribution of the averaged daily solar radiation and air temperature, the stochastic model satisfactorily simulated grain productivity, i.e., it was found that 10,604 kg ha(-1) is the most likely grain productivity, very similar to the productivity simulated by the deterministic model and for the real conditions based on a field experiment. © 2012 American Society of Agricultural and Biological Engineers.

The Relationship Between the Stay-Green Trait and Grain Yield in Elite Sorghum Hybrids Grown in a Range of Environments

The stay-green drought adaptation mechanism has been widely promoted as a way of improving grain yield and lodging resistance in sorghum [Sorghum bicolor (L.) Moench] and as a result has been the subject of many physiological and genetic studies. The relevance of these studies to elite sorghum hybrids is not clear given that they sample a limited number of environments and were conducted using inbred lines or relatively small numbers of experimental F-1 hybrids. In this study we investigated the relationship between stay-green and yield using data from breeding trials that sampled 1668 unique hybrid combinations and 23 environments whose mean yields varied from 2.3 to 10.5 t ha(-1). The strength and direction of the association between stay-green and grain yield varied with both environment and genetic background (male tester). The majority of associations were positive, particularly in environments with yields below 6 t ha(-1). As trial mean yield increased above 6 t ha(-1) there was a trend toward an increased number of negative associations; however, the number and magnitude of the positive associations were larger. Given that post-flowering drought is very commonly experienced by sorghum crops world wide and average yields are 1.2 and 2.5 t ha(-1) for the world and Australia, respectively, our results indicate that selection for stay-green in elite sorghum hybrids may be broadly beneficial for increasing yield in a wide range of environments.

Yield losses in grain sorghum due to rust infection

Although rust (caused by Puccinia purpurea) is a common disease in Australian grain sorghum crops, particularly late in the growing season (April onwards), its potential to reduce yield has not been quantified. Field trials were conducted in Queensland between 2003 and 2005 to evaluate the effect of sorghum rust on grain yield of two susceptible sorghum hybrids (Tx610 and Pride). Rust was managed from 28-35 days after sowing until physiological maturity by applying oxycarboxin (1 kg active ingredient/100 L of water/ha) every 10 days. When data were combined for the hybrids, yield losses ranged from 13.1% in 2005 to 3.2% in 2003 but differences in yield the between sprayed and unsprayed treatments were statistically significant (P a parts per thousand currency signaEuro parts per thousand 0.05) only in 2005. Final area under the disease progress curve (AUDPC) values reflected the yield losses in each year. The higher yield loss in 2005 can be attributed primarily to the early development of the rust epidemic and the higher inoculum levels in spreader plots at the time of planting of the trials.

Population dynamics of house mice in Queensland grain-growing areas

Context. Irregular plagues of house mice cause high production losses in grain crops in Australia. If plagues can be forecast through broad-scale monitoring or model-based prediction, then mice can be proactively controlled by poison baiting. Aims. To predict mouse plagues in grain crops in Queensland and assess the value of broad-scale monitoring. Methods. Regular trapping of mice at the same sites on the Darling Downs in southern Queensland has been undertaken since 1974. This provides an index of abundance over time that can be related to rainfall, crop yield, winter temperature and past mouse abundance. Other sites have been trapped over a shorter time period elsewhere on the Darling Downs and in central Queensland, allowing a comparison of mouse population dynamics and cross-validation of models predicting mouse abundance. Key results. On the regularly trapped 32-km transect on the Darling Downs, damaging mouse densities occur in 50% of years and a plague in 25% of years, with no detectable increase in mean monthly mouse abundance over the past 35 years. High mouse abundance on this transect is not consistently matched by high abundance in the broader area. Annual maximum mouse abundance in autumn–winter can be predicted (R2 = 57%) from spring mouse abundance and autumn–winter rainfall in the previous year. In central Queensland, mouse dynamics contrast with those on the Darling Downs and lack the distinct annual cycle, with peak abundance occurring in any month outside early spring.Onaverage, damaging mouse densities occur in 1 in 3 years and a plague occurs in 1 in 7 years. The dynamics of mouse populations on two transects ~70 km apart were rarely synchronous. Autumn–winter rainfall can indicate mouse abundance in some seasons (R2 = ~52%). Conclusion. Early warning of mouse plague formation in Queensland grain crops from regional models should trigger farm-based monitoring. This can be incorporated with rainfall into a simple model predicting future abundance that will determine any need for mouse control. Implications. A model-based warning of a possible mouse plague can highlight the need for local monitoring of mouse activity, which in turn could trigger poison baiting to prevent further mouse build-up.

Improving the prediction of odour impacts from meat chicken farms with detailed ventilation and odour data

Odour from meat chicken (broiler) farms is an environmental issue affecting the sustainable development of the chicken meat industry but is a normal part of broiler production. Odour plumes exhausted from broiler sheds interact with the environment, where dispersion and dilution of the odours varies constantly, especially diurnally. The potential for odour impacts is greatest when odour emission rates are high and/or when atmospheric dispersion and dilution of odour plumes is limited (i.e. during stable conditions). We continuously monitored ventilation rate, on-site weather conditions, atmospheric stability, and estimated odour concentration with an artificial olfaction system. Detailed inspection of odour emission rates at critical times, i.e. dawn, dusk and night time, revealed that maximum daily and batch odour emission rates are not necessarily the cause of odour impacts. Periods of lower odour emission rates on each day are more likely to correspond with odour impacts. Odour emission rates need to be measured at the times when odour impacts are most likely to occur, which is likely to be at night. Additionally, high resolution ventilation rate data should be sought after to improve odour emission models, especially at critical times of the day. Consultants, regulators and researchers need to give more thought to odour emission rates from meat chicken farms to improved prediction and management of odour impacts.