458 research outputs found
Root disease of cereals
Effects of nitrogen source on take-all, 82N34, 77E4. Take-all, cultivar, fertilizer, fungicide interactions, 87MT47, 87MT48, 87MT49. Take –all decline, 86MT7. Rhizoctonia root rot. Rhizoctonia patch and soil compaction, 87E28. Rhizoctonia patch and short chemical fallow, 87E3, 87E38. Rhizoctonia strains and paddock history, 87E31. Rhizoctonia root rot - host effects on strains, 87BA4, 86E30. Fusarium crown rot. Fusarium crown rot and cultivars, 87ME2, 87ME4, 87ME3 ( abandoned )
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Prediction of lignin content in ruminant diets and faecal samples using rapid analytical techniques
The measurement of lignin content in ruminant diet and faecal samples is important for 2 digestibility studies, but it is typically time consuming and costly. The work reported 3 involved correlation of traditional wet chemistry data with that from three rapid instrumental 4 techniques, Fourier Transform Infrared spectroscopy (FTIR), Conventional 5 Thermogravimteric Analysis (TGA) and High Resolution TGA (MaxRes TGA) to predict 6 lignin content of diets and faeces from digestibility trials. Calibration and performance data 7 indicated that the FTIR model was acceptable for screening whilst the Conventional and 8 MaxRes TGA predictions were of high accuracy for quantitative analysis. Cross validation 9 and model performance data revealed that MaxRes TGA provided the best performing 10 predictive model. This work showed that MaxRes TGA can accurately predict lignin content 11 in ruminant diet and faecal samples with distinct advantages over traditional wet chemistry, 12 namely the requirement for small sample size, ease of sample preparation, speed of analysis 13 and high sample throughput at considerably lower cost
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Core-periphery or decentralized? Topological shifts of specialized information on Twitter
In this paper we investigate shifts in Twitter network topology resulting from the type of information being shared. We identified communities matching areas of agricultural expertise and measured the core-periphery centralization of network formations resulting from users sharing generic versus specialized information. We found that centralization increases when specialized information is shared and that the network adopts decentralized formations as conversations become more generic. The results are consistent with classical diffusion models positing that specialized information comes with greater centralization, but they also show that users favor decentralized formations, which can foster community cohesion, when spreading specialized information is secondary
Growers’ risk perception and trust in control options for huanglongbing citrus-disease in Florida and California
Citrus huanglongbing disease is an acute bacterial disease that threatens the sustainability of citrus production across the world. In the USA, the Asian Citrus Psyllid (ACP) is responsible for spreading the disease. Successful suppression of HLB requires action against ACP at large spatial scales, i.e. growers must cooperate. In Florida and California, the regions in which citrus is grown have been split into management areas and growers are encouraged to coordinate spraying of insecticide across these (area-wide control). We surveyed growers from Florida and California to assess the consensus of opinions concerning issues that influence HLB management. Our results show that risk perception and trust in control options are central to the decision by growers on whether to join an area-wide control program. Growers’ perceptions on risk and control efficacy are influenced by information networks and observations about the state of the epidemic and psyllid populations. Researchers and extension agents were reported to have the largest influence on these perceptions. Differences in opinion between California and Florida growers as to the efficacy of treatments were largely a function of experience. A large proportion of growers identified failure of participation as a reason why participation in area-wide control might not occur
Reducing MCPA herbicide pollution at catchment scale using an agri-environmental scheme
Publication history: Accepted - 16 May 2022; Published online - 20 May 2022.In river catchments used as drinking water sources, high pesticide concentrations in abstracted waters require an expensive
treatment step prior to supply. The acid herbicide 2-methyl-4-chlorophenoxyacetic acid (MCPA) is particularly
problematic as it is highly mobile in the soil-water environment following application. Here, an agri-environmental
scheme (AES) was introduced to a large-scale catchment (384 km2) to potentially reduce the burden of pesticides in
the water treatment process. The main measure offered was contractor application of glyphosate by weed wiping as
a substitute for boom spraying of MCPA, supported by educational and advisory activities. A combined innovation applied
in the assessment was, i) a full before-after-control-impact (BACI) framework over four peak application seasons
(April to October 2018 to 2021) where a neighbouring catchment (386 km2) did not have an AES and, ii) an enhanced
monitoring approach where river discharge and MCPA concentrations were measured synchronously in each catchment.
During peak application periods the sample resolution was every 7 h, and daily during quiescent winter periods.
This sampling approach enabled flow- and time-weighted concentrations to be established, and a detailed record of
export loads. These loads were up to 0.242 kg km−2 yr−1, and over an order of magnitude higher than previously reported
in the literature. Despite this, and accounting for inter-annual and seasonal variations in river discharges, the
AES catchment indicated a reduction in both flow- and time-weighted MCPA concentration of up to 21% and 24%, respectively,
compared to the control catchment. No pollution swapping was detected. Nevertheless, the percentage of
MCPA occurrences above a 0.1 μg L−1 threshold did not reduce and so the need for treatment was not fully resolved.
Although the work highlights the advantages of catchment management approaches for pollution reduction in source
water catchments, it also indicates that maximising participation will be essential for future AES.This work was carried out as part of Source to Tap (IVA5018), a project supported by the European Union's INTERREG VA Programme, managed by the Special EU Programmes Body (SEUPB)
Nutrient status of cattle grazing systems in the western brazilian Amazon.
Low-input cultivated pastures to feed cattle have dominated land use after forest clearing for decades in the western Brazilian Amazon. This study was undertaken to help understand the inherent nutrient supply dynamics underwriting cattle performance on three farms in the state of Acre. We assessed soil chemical and physical properties associated over time with different land uses following forest clearing. This information permitted specifying a conceptual model of nutrient stocks and flows under the observed grazing system, which produced insights about the dynamics of soil nutrient degradation. Above ground forage mass, topsoil nutrient concentrations and soil bulk density were measured. Land covers were Brachiaria spp. grasses, a grass-Pueraria phaseoloides mix, cropland and forest. Most soil nutrient parameters initially decreased after clearing, gradually recovering over time with grass-only pastures; however, 20 yr-old pastures had 20% less forage mass. Most pasture system nutrients on these farms resided in topsoil and roots, where large stocks of mature forage supported soil fertility with recycled nutrients from litter. Estimates of partial topsoil nutrient balances were negative. This suggested that corresponding nutrient stocks and the accumulation of forage mass were probably maintained primarily through the sum of inflows from cattle excreta, the subsoil, soil organic matter, and litter mineralization with scant input of commercial fertilizer. Therefore, herd management to increase animal system productivity via higher stocking rates on vegetatively younger forage requires monitoring of nutrient stocks and flows and fertilization that assures replenishment of the nutrients extracted. Otherwise, rapid depletion of soil nutrient stocks will lead to system degradation and failure
Mechanism Design in Social Networks
This paper studies an auction design problem for a seller to sell a commodity
in a social network, where each individual (the seller or a buyer) can only
communicate with her neighbors. The challenge to the seller is to design a
mechanism to incentivize the buyers, who are aware of the auction, to further
propagate the information to their neighbors so that more buyers will
participate in the auction and hence, the seller will be able to make a higher
revenue. We propose a novel auction mechanism, called information diffusion
mechanism (IDM), which incentivizes the buyers to not only truthfully report
their valuations on the commodity to the seller, but also further propagate the
auction information to all their neighbors. In comparison, the direct extension
of the well-known Vickrey-Clarke-Groves (VCG) mechanism in social networks can
also incentivize the information diffusion, but it will decrease the seller's
revenue or even lead to a deficit sometimes. The formalization of the problem
has not yet been addressed in the literature of mechanism design and our
solution is very significant in the presence of large-scale online social
networks.Comment: In The Thirty-First AAAI Conference on Artificial Intelligence, San
Francisco, US, 04-09 Feb 201
Quantifying MCPA load pathways at catchment scale using high temporal resolution data
Publication history: Accepted - 21 May 2022; Published online - 24 May 2022.Detection of the agricultural acid herbicide MCPA (2-methyl-4-chlorophenoxyacetic acid) in drinking water
source catchments is of growing concern, with economic and environmental implications for water utilities and
wider ecosystem services. MCPA is poorly adsorbed to soil and highly mobile in water, but hydrological pathway
processes are relatively unknown at the catchment scale and limited by coarse resolution data. This understanding
is required to target mitigation measures and to provide a framework to monitor their effectiveness. To
address this knowledge gap, this study reports findings from river discharge and synchronous MCPA concentration
datasets (continuous 7 hour and with additional hourly sampling during storm events) collected over a 7
month herbicide spraying season. The study was undertaken in a surface (source) water catchment (384 km2—of
which 154 km2 is agricultural land use) in the cross-border area of Ireland. Combined into loads, and using two
pathway separation techniques, the MCPA data were apportioned into event and baseload components and the
former was further separated to quantify a quickflow (QF) and other event pathways. Based on the 7 hourly
dataset, 85.2 kg (0.22 kg km 2 by catchment area, or 0.55 kg km 2 by agricultural area) of MCPA was exported
from the catchment in 7 months. Of this load, 87.7 % was transported via event flow pathways with 72.0 %
transported via surface dominated (QF) pathways. Approximately 12 % of the MCPA load was transported via
deep baseflows, indicating a persistence in this delayed pathway, and this was the primary pathway condition
monitored in a weekly regulatory sampling programme. However, overall, the data indicated a dominant acute,
storm dependent process of incidental MCPA loss during the spraying season. Reducing use and/or implementing
extensive surface pathway disconnection measures are the mitigation options with greatest potential, the success
of which can only be assessed using high temporal resolution monitoring techniques.This work was carried out as part of Source to Tap (IVA5018), a
project supported by the European Union’s INTERREG VA Programme,
managed by the Special EU Programmes Body (SEUPB)
Mitigating the effects of omission errors on area and area change estimates
Information on Earth's land surface and change over time has never been easier to obtain, but making informed decisions to manage land well necessitates that this information is accurate and precise. In recent years, due largely to the inevitability of classification errors in remote sensing-based maps and the marked effects of these errors on subsequent area estimates, sample-based area estimates of land cover and land change have increased in importance and use. Area estimation of land cover and change by sampling is often made more efficient by a priori knowledge of the study area to be analyzed (e.g., stratification). Satellite data, obtained free of cost for virtually all of Earth's land surface, provide an excellent source for constructing landscape stratifications in the form of maps. Errors of omission, defined as sample units observed as land change but mapped as a stable class, may introduce considerable uncertainty in parameter estimates obtained from the sample data (e.g., area estimates of land change). The effects of omission errors are exacerbated in situations where the area of intact forest is large relative to the area of forest change, a common situation in countries that seek results-based payments for reductions in deforestation and associated carbon emissions. The presence of omission errors in such situations can preclude the acquisition of statistically valid evidence of a reduction in deforestation, and thus prevent payments. International donors and countries concerned with mitigating the effects of climate change are looking for guidance on how to reduce the effects of omission errors on area estimates of land change. This article presents the underlying reasons for the effects of omission errors on area estimates, case studies highlighting real-world examples of these effects, and proposes potential solutions. Practicable approaches to efficiently splitting large stable strata are presented that may reduce the effects of omission errors and immediately improve the quality of estimates. However, more research is needed before further recommendations can be provided on how to contain, mitigate and potentially eliminate the effects of omissions errors. © 2019 Elsevier Inc.This research was funded by support from the NASA Carbon Monitoring System ( NNX16AP26G ) and USGS/SilvaCarbon to Boston University (PI Pontus Olofsson). M.J. Sanz was supported by the Spanish Government through MarÃa de Maeztu excellence accreditation MDM-2017-0714
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