Simulation of site-specific irrigation control strategies with sparse input data

Crop and irrigation water use efficiencies may be improved by managing irrigation application timing and volumes using physical and agronomic principles. However, the crop water requirement may be spatially variable due to different soil properties and genetic variations in the crop across the field. Adaptive control strategies can be used to locally control water applications in response to in-field temporal and spatial variability with the aim of maximising both crop development and water use efficiency. A simulation framework ‘VARIwise’ has been created to aid the development, evaluation and management of spatially and temporally varied adaptive irrigation control strategies (McCarthy et al., 2010). VARIwise enables alternative control strategies to be simulated with different crop and environmental conditions and at a range of spatial resolutions. An iterative learning controller and model predictive controller have been implemented in VARIwise to improve the irrigation of cotton. The iterative learning control strategy involves using the soil moisture response to the previous irrigation volume to adjust the applied irrigation volume applied at the next irrigation event. For field implementation this controller has low data requirements as only soil moisture data is required after each irrigation event. In contrast, a model predictive controller has high data requirements as measured soil and plant data are required at a high spatial resolution in a field implementation. Model predictive control involves using a calibrated model to determine the irrigation application and/or timing which results in the highest predicted yield or water use efficiency. The implementation of these strategies is described and a case study is presented to demonstrate the operation of the strategies with various levels of data availability. It is concluded that in situations of sparse data, the iterative learning controller performs significantly better than a model predictive controller

Air pollution and livestock production

The air in a livestock farming environment contains high concentrations of dust particles and gaseous pollutants. The total inhalable dust can enter the nose and mouth during normal breathing and the thoracic dust can reach into the lungs. However, it is the respirable dust particles that can penetrate further into the gas-exchange region, making it the most hazardous dust component. Prolonged exposure to high concentrations of dust particles can lead to respiratory health issues for both livestock and farming staff. Ammonia, an example of a gaseous pollutant, is derived from the decomposition of nitrous compounds. Increased exposure to ammonia may also have an effect on the health of humans and livestock. There are a number of technologies available to ensure exposure to these pollutants is minimised. Through proactive means, (the optimal design and management of livestock buildings) air quality can be improved to reduce the likelihood of risks associated with sub-optimal air quality. Once air problems have taken hold, other reduction methods need to be applied utilising a more reactive approach. A key requirement for the control of concentration and exposure of airborne pollutants to an acceptable level is to be able to conduct real-time measurements of these pollutants. This paper provides a review of airborne pollution including methods to both measure and control the concentration of pollutants in livestock buildings

Non-destructive soluble solids content determination for ‘Rocha’ Pear Based on VIS-SWNIR spectroscopy under ‘Real World’ sorting facility conditions

In this paper we report a method to determine the soluble solids content (SSC) of 'Rocha' pear (Pyrus communis L. cv. Rocha) based on their short-wave NIR reflectance spectra (500-1100 nm) measured in conditions similar to those found in packinghouse fruit sorting facilities. We obtained 3300 reflectance spectra from pears acquired from different lots, producers and with diverse storage times and ripening stages. The macroscopic properties of the pears, such as size, temperature and SSC were measured under controlled laboratory conditions. For the spectral analysis, we implemented a computational pipeline that incorporates multiple pre-processing techniques including a feature selection procedure, various multivariate regression models and three different validation strategies. This benchmark allowed us to find the best model/preproccesing procedure for SSC prediction from our data. From the several calibration models tested, we have found that Support Vector Machines provides the best predictions metrics with an RMSEP of around 0.82 ∘ Brix and 1.09 ∘ Brix for internal and external validation strategies respectively. The latter validation was implemented to assess the prediction accuracy of this calibration method under more 'real world-like' conditions. We also show that incorporating information about the fruit temperature and size to the calibration models improves SSC predictability. Our results indicate that the methodology presented here could be implemented in existing packinghouse facilities for single fruit SSC characterization.Funding Agency CEOT strategic project UID/Multi/00631/2019 project OtiCalFrut ALG-01-0247-FEDER-033652 Ideias em Caixa 2010, CAIXA GERAL DE DEPOSITOS Fundacao para a Ciencia e a Tecnologia (Ciencia)info:eu-repo/semantics/publishedVersio

Organic residues - a resource for arable soils

An increased recirculation of urban organic residues to arable soils has several environmental benefits, but there is a need for reliable test systems to ensure that soil quality is maintained. In this thesis, soil microbial, chemical and physical properties were included in an integrated evaluation to reflect the positive and negative effects of amending arable soils with organic residues. Efficient statistical tools and methods to describe intrinsic spatial variation are important when evaluating soil data. A new method was developed, combining near infrared reflectance (NIR) spectroscopy with principal component analysis (PCA). The first principal component (PC1) of NIR data described spatial soil variation better than the conventional soil variables total carbon, clay content and pH. A long-term field trial was established in which the soil was amended annually with organic residues (compost, biogas residues, sewage sludge) and fertilizers (pig manure, cow manure and mineral fertilizer, NPS). Annual measurements of soil and crop quality as well as yield revealed that biogas residues performed best among the organic residues. It improved several important microbiological properties, such as substrate-induced respiration (SIR) and potential ammonium oxidation (PAO), and it compared well with mineral fertilizer in terms of grain quality and harvest yield. Altogether, the results from the field trial showed no negative effects from any of the organic residues. Short- and moderately long-term effects of wood ash and compost on potential denitrification activity (PDA) and PAO were evaluated in a laboratory incubation experiment. Wood ash application had a profound toxic effect on PDA both in the short- and long-term. This toxic effect was mitigated when compost was added to the soil

TRIAD - Preliminary design of an operational earth resources survey system Final report

Design of operational earth resources survey syste

2011 Strategic roadmap for Australian research infrastructure

The 2011 Roadmap articulates the priority research infrastructure areas of a national scale (capability areas) to further develop Australia’s research capacity and improve innovation and research outcomes over the next five to ten years. The capability areas have been identified through considered analysis of input provided by stakeholders, in conjunction with specialist advice from Expert Working Groups   It is intended the Strategic Framework will provide a high-level policy framework, which will include principles to guide the development of policy advice and the design of programs related to the funding of research infrastructure by the Australian Government. Roadmapping has been identified in the Strategic Framework Discussion Paper as the most appropriate prioritisation mechanism for national, collaborative research infrastructure. The strategic identification of Capability areas through a consultative roadmapping process was also validated in the report of the 2010 NCRIS Evaluation. The 2011 Roadmap is primarily concerned with medium to large-scale research infrastructure. However, any landmark infrastructure (typically involving an investment in excess of $100 million over five years from the Australian Government) requirements identified in this process will be noted. NRIC has also developed a ‘Process to identify and prioritise Australian Government landmark research infrastructure investments’ which is currently under consideration by the government as part of broader deliberations relating to research infrastructure. NRIC will have strategic oversight of the development of the 2011 Roadmap as part of its overall policy view of research infrastructure

From dust bowl to dust bowl:soils are still very much a frontier of science

When the Soil Science Society of America was created, 75 yr ago, the USA was suffering from major dust storms, causing the loss of enormous amounts of topsoil as well as human lives. These catastrophic events reminded public officials that soils are essential to society’s well-being. The Soil Conservation Service was founded and farmers were encouraged to implement erosion mitigation practices. Still, many questions about soil processes remained poorly understood and controversial. In this article, we argue that the current status of soils worldwide parallels that in the USA at the beginning of the 20th century. Dust bowls and large-scale soil degradation occur over vast regions in a number of countries. Perhaps more so even than in the past, soils currently have the potential to affect populations critically in several other ways as well, from their effect on global climate change, to the toxicity of brownfield soils in urban settings. Even though our collective understanding of soil processes has experienced significant advances since 1936, many basic questions still remain unanswered, for example whether or not a switch to no-till agriculture promotes C sequestration in soils, or how to account for microscale heterogeneity in the modeling of soil organic matter transformation. Given the enormity of the challenges raised by our (ab)uses of soils, one may consider that if we do not address them rapidly, and in the process heed the example of U.S. public officials in the 1930s who took swift action, humanity may not get a chance to explore other frontiers of science in the future. From this perspective, insistence on the fact that soils are critical to life on earth, and indeed to the survival of humans, may again stimulate interest in soils among the public, generate support for soil research, and attract new generations of students to study soils

Food Physical Chemistry and Biophysical Chemistry

Food Physical Chemistry is considered to be a branch of Food Chemistry^1,2^ concerned with the study of both physical and chemical interactions in foods in terms of physical and chemical principles applied to food systems, as well as the applications of physical/chemical techniques and instrumentation for the study of foods^3,4,5,6^. This field encompasses the "physiochemical principles of the reactions and conversions that occur during the manufacture, handling, and storage of foods"^7^. Two rapidly growing, related areas are Food Biotechnology and Food Biophysical Chemistry. 
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