Zoonotic origin and transmission of Middle East respiratory syndrome coronavirus in the UAE

Since the emergence of Middle East respiratory syndrome coronavirus (MERS‐CoV) in 2012, there have been a number of clusters of human‐to‐human transmission. These cases of human‐to‐human transmission involve close contact and have occurred primarily in healthcare settings, and they are suspected to result from repeated zoonotic introductions. In this study, we sequenced whole MERS‐CoV genomes directly from respiratory samples collected from 23 confirmed MERS cases in the United Arab Emirates (UAE). These samples included cases from three nosocomial and three household clusters. The sequences were analysed for changes and relatedness with regard to the collected epidemiological data and other available MERS‐CoV genomic data. Sequence analysis supports the epidemiological data within the clusters, and further, suggests that these clusters emerged independently. To understand how and when these clusters emerged, respiratory samples were taken from dromedary camels, a known host of MERS‐CoV, in the same geographic regions as the human clusters. Middle East respiratory syndrome coronavirus genomes from six virus‐positive animals were sequenced, and these genomes were nearly identical to those found in human patients from corresponding regions. These data demonstrate a genetic link for each of these clusters to a camel and support the hypothesis that human MERS‐CoV diversity results from multiple zoonotic introductions.     

Bacterial degradation of fungicide captan

The phthalimide fungicide captan has been widely used to control plant pathogenic fungi. A strain of Bacillus circulans utilized the fungicide captan as sole source of carbon and energy. The organism degraded captan by a pathway involving its initial hydrolysis to yield cis-1,2,3,6-tetrahydrophthalimide, a compound without fungicidal activity. The formation of this compound was confirmed by HPLC, IR, NMR, and mass spectral analysis. The results also revealed that cis-1,2,3,6-tetrahydrophthalimide was further degraded to o-phthalic acid by a protocatechuate pathway. These findings indicated that there was a complete mineralization of fungicide captan by B. circulans.     

Identifying important factors influencing corn yield and grain quality variability using artificial neural networks

Soil, landscape and hybrid factors are known to influence yield and quality of corn (Zea mays L.). This study employed artificial neural network (ANN) analysis to evaluate the relative importance of selected soil, landscape and seed hybrid factors on yield and grain quality in two Illinois, USA fields. About 7 to 13 important factors were identified that could explain from 61% to 99% of the observed yield or quality variability in the study site-years. Hybrid was found to be the most important factor overall for quality in both fields, and for yield as well in Field 1. The relative importance of soil and landscape factors for corn yield and quality and their relationships differed by hybrid and field. Cation exchange capacity (CEC) and relative elevation were consistently identified as among the top four most important soil and landscape factors for both corn yield and quality in both fields in 2000. Aspect and Zn were among the top five most important factors in Fields 1 and 2, respectively. Compound topographic index (CTI), profile curvature and tangential curvature were, in general, not important in the study site-years. The response curves generated by the ANN models were more informative than simple correlation coefficients or coefficients in multiple regression equations. We conclude that hybrid was more important than soil and landscape factors for consideration in precision crop management, especially when grain quality was a management objective.     

Acetochlor Persistence in Surface and Subsurface Soil Samples

Two cadmium-resistant bacteria, Ralstonia sp. TAK1 and Arthrobacter sp. TM6, produced exopolymers that promoted cadmium solubilization in contaminated soil. The enhancement of cadmium uptake and accumulation in a monocot (Vetiveria nemoralis, vetiver grass) and a dicot (Ocimum gratissimum, African basil) was investigated in a greenhouse study. Compared with the uninoculated control, Ralstonia sp. TAK1 and Arthrobacter sp. TM6 increased cadmium accumulation in the roots and shoots of V. nemoralis. These cadmium-resistant bacteria increased the cadmium content of whole V. nemoralis plants similarly to ethylenediaminetetraacetic acid (EDTA) treatment alone. In contrast, only Arthrobacter sp. TM6 enhanced cadmium accumulation in the roots and shoots of O. gratissimum. The highest cadmium content of whole O. gratissimum plants was observed when the plant was treated with EDTA following treatment with Arthrobacter sp. TM6. The phytoextraction coefficient and translocation factor (TF) of bacteria-inoculated V. nemoralis were higher than those of O. gratissimum. Arthrobacter sp. TM6 increased the phytoextraction coefficients and TFs in V. nemoralis and O. gratissimum. These results indicate that Arthrobacter sp. TM6 and both tested plant species promote cadmium phytoextraction in contaminated soil.     

Combining chlorophyll meter readings and high spatial resolution remote sensing images for in-season site-specific nitrogen management of corn

The chlorophyll meter (CM) has been commonly used for in-season nitrogen (N) management of corn (Zea mays L.). Nevertheless, it has limited potential for site-specific N management in large fields due to difficulties in using it to generate N status maps. The objective of this study was to determine how well CM readings can be estimated using aerial hyper-spectral and simulated multi-spectral remote sensing images at different corn growth stages. Two field experiments were conducted in Minnesota, USA during 2005 involving different N application rates and timings on a corn-soybean [Glycine max (L.) Merr.] rotation field and a corn-corn rotation field. Four flights were made during the growing season using the AISA Eagle Hyper-spectral Imager and CM readings were collected at four or five different growth stages. The results indicated that single multi-spectral and hyper-spectral band or vegetation index could explain 64–86% and 73–88% of the variability in CM readings, respectively, except at growth stage V9 in the corn-soybean rotation field where no band or vegetation index could explain more than 37% of the variability in CM readings. Multiple regression analysis demonstrated that the combination of 2–4 broad-bands or 3–8 narrow-bands could explain 41–92% or 61–94% of the variability in CM readings across the two fields and different corn growth stages investigated. It was concluded that the combination of CM readings with high spatial resolution hyper-spectral or multi-spectral remote sensing images can overcome the limitations of using them individually, thus offering a practical solution to N deficiency detection and possibly in-season site-specific N management in large continuous corn fields or at later stages in corn-soybean rotation fields.     

Simulated long-term nitrogen losses for a midwestern agricultural watershed in the United States

Adequate knowledge on the movement of nutrients under various agricultural practices is essential for developing remedial measures to reduce nonpoint source pollution. Mathematical models, after extensive calibration and validation, are useful to derive such knowledge and to identify site-specific alternative agricultural management practices. A spatial-process model that uses GIS and ADAPT, a field scale daily time-step continuous water table management model, was calibrated and validated for flow and nitrate-N discharges from a 365 ha agricultural watershed in central Iowa, in the Midwestern United States. This watershed was monitored for nitrate-N losses from 1991 to 1997. Spatial patterns in crops, topography, fertilizer applications and climate were used as input to drive the model. The first half of the monitored data was used for calibration and the other half was used in validation of the model. For the calibration period, the observed and predicted flow and nitrate-N discharges were in excellent agreement with r² values of 0.88 and 0.74, respectively. During the validation period, the observed and predicted flow and nitrate-N discharges were in good agreement with r² values of 0.71 and 0.50, respectively. For all 6 years of data, the observed annual nitrate-N losses of 26 kg ha⁻¹ for the entire simulation were in excellent agreement with predicted nitrate-N losses of 24.2 kg ha⁻¹. The calibrated model was used to investigate the long-term impacts of nitrate-N losses to changes in the rate and timing of fertilizer application. Results indicate that nitrate-N losses were sensitive to rate and timing of fertilizer application. Modeled annual nitrate-N losses showed a 17% reduction in nitrate-N losses by reducing the fertilizer application rate by 20% and switching the application timing from fall to spring. Further reductions in nitrate-N losses require conversion of row cropland to pasture and/or replacement of continuous corn or corn–soybean rotation systems with alternative crops.     

Effects of Stocking Size and Density of Tilapia on Macrobrachium rosenbergii in Polyculture

Studies were conducted to determine the effect of stocking size and density of prawns in polyculture.
In one experiment, postlarval prawns (av. wt. 0.02 g) were stocked in six 0.02 ha earthen ponds at 35,00O/ha. Two ponds were stocked with tilapia fry (av. wt. 0.14 g) and two were stocked with tilapia fingerlings (av. wt. 30.1 g), each at 10,000/ha. Two control ponds had no tilapia. Tilipia stocking size had no effect on prawn growth. Mean weight of prawns after 70 days of culture ranged from a low of 4.5 g when cultured with tilapia fingerlings to a high of 6.6 when cultured in monoculture. Prawn survival was adversely affected by tilapia fry. Average prawn survival in tilapia fry ponds was 65% compared to 75% and 91%, respectively, in tilapia fingerling and monoculture ponds.
In a second experiment, postlarval prawns were stocked in nine 0.02 ha earthen ponds at 40,000/ ha. Six ponds were stocked with 30 g tilapia fingerlings, three at 5,000/ha and three at 15,000/ha. Three control ponds received prawns only. After 100 days of culture, prawn weight ranged from an average of 15.9 g in monoculture ponds to 11.5 g in polyculture ponds. Survival was highest (93.8%) in low density polyculture ponds. Survival was lowest (85.6%) in prawn monoculture ponds. Tilapia reproduction had a negative impact on shrimp production.