Veterinary Science Collected Works - Research Publications
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ItemRoots' Drought Adaptive Traits in Crop Improvement.(MDPI AG, 2022-08-30)Drought is one of the biggest concerns in agriculture due to the projected reduction of global freshwater supply with a concurrent increase in global food demand. Roots can significantly contribute to improving drought adaptation and productivity. Plants increase water uptake by adjusting root architecture and cooperating with symbiotic soil microbes. Thus, emphasis has been given to root architectural responses and root-microbe relationships in drought-resilient crop development. However, root responses to drought adaptation are continuous and complex processes and involve additional root traits and interactions among themselves. This review comprehensively compiles and discusses several of these root traits such as structural, physiological, molecular, hydraulic, anatomical, and plasticity, which are important to consider together, with architectural changes, when developing drought resilient crop varieties. In addition, it describes the significance of root contribution in improving soil structure and water holding capacity and its implication on long-term resilience to drought. In addition, various drought adaptive root ideotypes of monocot and dicot crops are compared and proposed for given agroclimatic conditions. Overall, this review provides a broader perspective of understanding root structural, physiological, and molecular regulators, and describes the considerations for simultaneously integrating multiple traits for drought tolerance and crop improvement, under specific growing environments.
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ItemResearch Progress on Greenhouse Gas Emissions From Livestock in Sub-Saharan Africa Falls Short of National Inventory Ambitions(Frontiers Media SA, 2022-01-01)Livestock are an important source of livelihoods in agricultural systems in sub-Saharan Africa (SSA), while also being the largest source of national greenhouse gas (GHG) emissions in most African countries. As a consequence, there is a critical need for data on livestock GHG sources and sinks to develop national inventories, as well as conduct baseline measurements and intervention testing to mitigate GHG emissions and meet ambitious national climate goals. Our objective was to review studies on GHG emissions from livestock systems in SSA, as well as soil carbon storage in livestock-dominated systems (i.e., grasslands and rangelands), to evaluate best current data and suggest future research priorities. To this end, we compiled studies from SSA that determined emission factors (EFs) for enteric methane and manure emissions, along with studies on soil organic carbon (SOC) stocks in SSA. We found that there has been limited research on livestock GHG emissions and SOC relative to national ambitions for climate change mitigation in SSA. Enteric methane emission factors (EFs) in low productivity cattle systems may be lower than IPCC Tier 1 default EFs, whereas small ruminants (i.e. sheep and goats) had higher EFs compared to IPCC Tier 1 EFs. Manure EFs were equal to or lower than IPCC Tier 1 EFs for deposited manure (while grazing), manure applied as fertilizer, and manure management. SOC stocks for grasslands and rangelands in SSA show broad agreement with IPCC estimates, but there was a strong geographic bias and many studies did not report soil type, bulk density, or SOC stocks at >30 cm depth. In general, the largest data gaps included information for manure (quantity, quality, management), small ruminants, agropastoral/pastoralist systems, and in general from West Africa. Future research should focus on filling major data gaps on locally appropriate mitigation interventions and improving livestock activity data for developing Tier 2 GHG inventories in SSA. At the science-policy interface, all parties would benefit from enhanced coordination within the research community and between researchers and African governments to improve Tier 2 inventories and harmonize measurement for mitigation in livestock systems in SSA.
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ItemApplying C:N ratio to assess the rationality of estimates of carbon sequestration in terrestrial ecosystems and nitrogen budgets(Springer Science and Business Media LLC, 2022-12)Abstract Carbon (C) sequestration in terrestrial ecosystems needs to ensure the reactive nitrogen (Nr) supply. However, the organic C:N ratio is rarely considered in both estimates of C sequestration in terrestrial ecosystems and N budget at regional and global scale. Here we propose an approach for extracting Nr sequestrated in terrestrial ecosystems with C (termed as Nrc) from N budget and then assessing the rationality of estimates of C sequestration in terrestrial ecosystems and N budgets by using the sequestrated organic C:N ratio as a criterion. We extracted Nrc from the N budget of IPCC AR5 at global scale and Chinese N budget (Proc Natl Acad Sci (USA) 112:8792, 2015) at regional scale based on the assumptions that there is no net Nr accumulation in agricultural products and no net Nr (except N2O) accumulation in the atmosphere at annual temporal scale, and N2O is not involved in biological processes. By taking the C sequestration in terrestrial ecosystems from C budget of IPCC AR5 (2.1 Pg C/yr during 2000–2009) to assess the N budget from the same report, the organic C:N ratios calculated by the Nrc extracted from both the upper ranges and averages of Nr input and output in global N budgets of IPCC AR5 fell outside the rational range of organic C:N ratio, but the organic C:N ratio (=31) calculated by the Nrc (68.1 Tg N/yr) extracted from the lower ranges of the N budget fell very well into the range of organic C:N ratio in global terrestrial ecosystems. Nrc extracted from Chinese N budget was 11.6 Tg N/yr in 2010, which could be combined with C into Chinese terrestrial ecosystems in a range between 0.14–0.66 Pg C/yr with a robust estimate of 0.36 Pg C/yr by applying the global terrestrial ecosystem sequestrated organic C:N ratio to calculation. The results indicate that the proposed approach for extracting Nrc from N budget works well. Checking the estimated organic C:N ratio in terrestrial ecosystems will help to assess whether the C and/or N budgets are rational or not. Graphical abstract
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ItemCorrection: Applying C:N ratio to assess the rationality of estimates of carbon sequestration in terrestrial ecosystems and nitrogen budgets(Springer Science and Business Media LLC, 2022-12)
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ItemReducing Calf Mortality in Ethiopia(MDPI, 2022-08)Morbidity and mortality of young stock present economic and production challenges to livestock producers globally. In Ethiopia, calf morbidity and mortality rates, particularly due to diarrhea and respiratory disease, are high, limiting production, incomes, and the ability of farmers to improve their livelihoods. In this paper, we present findings from the combined experience of the Young Stock Mortality Reduction Consortium, which conducted epidemiological and intervention testing in calves across three production systems. This innovative alliance identified Cryptosporidium parvum and E. Coli K99 as the most common causes of diarrhea in pastoral and peri-urban calves; Strongyloides spp. as the most common fecal parasite in mixed crop-livestock and peri-urban calves; and bovine adenovirus, parainfluenza virus-3, and bovine respiratory syncytial virus as the most common respiratory pathogens in peri-urban calves. Furthermore, by improving producer knowledge with respect to fundamental livestock husbandry, feeding, housing, and neonatal care practices, calf mortality risk across production systems was reduced by 31.4 to 71.4% compared to baseline (between 10.5 and 32.1%), whereas risk of diarrhea was reduced by 52.6-75.3% (baseline between 11.4 and 30.4%) and risk of respiratory disease was reduced by 23.6-80.8% (baseline between 3.3 and 16.3%). These findings have informed scaling strategies and can potentially contribute to improved livestock productivity and human livelihoods in Ethiopia.
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ItemCombining NDVI and Bacterial Blight Score to Predict Grain Yield in Field Pea.(Frontiers Media SA, 2022)Field pea is the most commonly grown temperate pulse crop, with close to 15 million tons produced globally in 2020. Varieties improved through breeding are important to ensure ongoing improvements in yield and disease resistance. Genomic selection (GS) is a modern breeding approach that could substantially improve the rate of genetic gain for grain yield, and its deployment depends on the prediction accuracy (PA) that can be achieved. In our study, four yield trials representing breeding lines' advancement stages of the breeding program (S0, S1, S2, and S3) were assessed with grain yield, aerial high-throughput phenotyping (normalized difference vegetation index, NDVI), and bacterial blight disease scores (BBSC). Low-to-moderate broad-sense heritability (0.31-0.71) and narrow-sense heritability (0.13-0.71) were observed, as the estimated additive and non-additive genetic components for the three traits varied with the different models fitted. The genetic correlations among the three traits were high, particularly in the S0-S2 stages. NDVI and BBSC were combined to investigate the PA for grain yield by univariate and multivariate GS models, and multivariate models showed higher PA than univariate models in both cross-validation and forward prediction methods. A 6-50% improvement in PA was achieved when multivariate models were deployed. The highest PA was indicated in the forward prediction scenario when the training population consisted of early generation breeding stages with the multivariate models. Both NDVI and BBSC are commonly used traits that could be measured in the early growth stage; however, our study suggested that NDVI is a more useful trait to predict grain yield with high accuracy in the field pea breeding program, especially in diseased trials, through its incorporation into multivariate models.
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ItemAlleviation of cadmium toxicity in Zea mays L. through up-regulation of growth, antioxidant defense system and organic osmolytes under calcium supplementation.(Public Library of Science (PLoS), 2022)Calcium (Ca) is a macronutrient and works as a modulator to mitigate oxidative stress induced by heavy metals. In this study, we investigated the role of Ca to ameliorate the Cd toxicity in Zea mays L. by modulating the growth, physio-biochemical traits, and cellular antioxidant defense system. Maize genotype Sahiwal-2002 was grown under a controlled glasshouse environment with a day/night temperature of 24 ± 4°C/14 ± 2°C in a complete randomized design with three replications and two Cd levels as (0 and 150 μM) and six regimes of Ca (0, 0.5, 1, 2.5, 5, and 10 mM). Maize seedlings exposed to Cd at 150 μM concentration showed a notable decrease in growth, biomass, anthocyanins, chlorophylls, and antioxidant enzymes activities. A higher level of Cd (150 μM) also caused an upsurge in oxidative damage observed as higher electrolyte leakage (increased membrane permeability), H2O2 production, and MDA accumulation. Supplementation of Ca notably improved growth traits, photosynthetic pigments, cellular antioxidants (APX, POD, and ascorbic acid), anthocyanins, and levels of osmolytes. The significant improvement in the osmolytes (proteins and amino acids), and enzymatic antioxidative defense system enhanced the membrane stability and mitigated the damaging effects of Cd. The present results concluded that exogenously applied Ca potentially improve growth by regulating antioxidants and enabling maize plants to withstand the Cd toxicity.
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ItemWelfare Through Competence: A Framework for Animal-Centric Technology Design(FRONTIERS MEDIA SA, 2022-06-30)Digital technologies offer new ways to ensure that animals can lead a good life in managed settings. As interactive enrichment and smart environments appear in zoos, farms, shelters, kennels and vet facilities, it is essential that the design of such technologies be guided by clear, scientifically-grounded understandings of what animals need and want, to be successful in improving their wellbeing. The field of Animal-Computer Interaction proposes that this can be achieved by centering animals as stakeholders in technology design, but there remains a need for robust methods to support interdisciplinary teams in placing animals' interests at the heart of design projects. Responding to this gap, we present the Welfare through Competence framework, which is grounded in contemporary animal welfare science, established technology design practices and applied expertise in animal-centered design. The framework brings together the "Five Domains of Animal Welfare" model and the "Coe Individual Competence" model, and provides a structured approach to defining animal-centric objectives and refining them through the course of a design project. In this paper, we demonstrate how design teams can use this framework to promote positive animal welfare in a range of managed settings. These much-needed methodological advances contribute a new theoretical foundation to debates around the possibility of animal-centered design, and offer a practical agenda for creating technologies that support a good life for animals.
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ItemAutomated hyperspectral vegetation index derivation using a hyperparameter optimisation framework for high-throughput plant phenotyping.(Wiley, 2022-03)Hyperspectral vegetation indices (VIs) are widely deployed in agriculture remote sensing and plant phenotyping to estimate plant biophysical and biochemical traits. However, existing VIs consist mainly of simple two-band indices that limit the net performance and often do not generalise well for traits other than those for which they were originally designed. We present an automated hyperspectral vegetation index (AutoVI) system for the rapid generation of novel two- to six-band trait-specific indices in a streamlined process covering model selection, optimisation and evaluation, driven by the tree parzen estimator algorithm. Its performance was tested in generating novel indices to estimate chlorophyll and sugar contents in wheat. Results showed that AutoVI can rapidly generate complex novel VIs (at least a four-band index) that correlated strongly (R2 > 0.8) with measured chlorophyll and sugar contents in wheat. Automated hyperspectral vegetation index-derived indices were used as features in simple and stepwise multiple linear regressions for chlorophyll and sugar content estimation, and outperformed the results achieved with the existing 47 VIs and those provided using partial least squares regression. The AutoVI system can deliver novel trait-specific VIs readily adoptable to high-throughput plant phenotyping platforms and should appeal to plant scientists and breeders. A graphical user interface for the AutoVI is provided here.
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ItemSniffing out what Australians know and believe about Drug Detector Dogs(ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2022-08-24)The ways in which drugs are policed, differs from country to country, with Drug Detector Dogs (DDDs) a commonly used detection strategy in Australia. However, their effectiveness has been scrutinized by Australian media and research. Despite this, their work and lives "on the job" continue to be portrayed in a positive light on popular television shows such as Border Security. The aim of the current study was to ascertain public perceptions and knowledge surrounding DDDs using a sample of 129 Australians. Results revealed participants believed DDDs were equally as interesting and as happy as companion dogs. However, while there was general support for both dog roles in human lives, participants were relatively less supportive of the use of DDDs. Importantly, findings suggest general Australians have little awareness of the lives of DDDs "off the job," including housing and handling practices that directly impact animal welfare. We suggest that greater transparency around these aspects of the dogs' lives and welfare experience be made publicly available so that the DDD industry can maintain their social license to operate.