Escherichia coli inactivation kinetics in anaerobic digestion of dairy manure under moderate, mesophilic and thermophilic temperatures

Batch anaerobic digestion experiments using dairy manure as feedstocks were performed at moderate (25°C), mesophilic (37°C), and thermophilic (52.5°C) temperatures to understand E. coli, an indicator organism for pathogens, inactivation in dairy manure. Incubation periods at 25, 37, and 52.5°C, were 61, 41, and 28 days respectively. Results were used to develop models for predicting E. coli inactivation and survival in anaerobic digestion. For modeling we used the decay of E. coli at each temperature to calculate the first-order inactivation rate coefficients, and these rates were used to formulate the time - temperature - E. coli survival relationships. We found the inactivation rate coefficient at 52.5°C was 17 and 15 times larger than the inactivation rate coefficients at 25 and 37°C, respectively. Decimal reduction times (D10 ; time to achieve one log removal) at 25, 37, and 52.5°C, were 9 -10, 7 - 8 days, and \u3c 1 day, respectively. The Arrhenius correlation between inactivation rate coefficients and temperatures over the range 25 -52.5°C was developed to understand the impacts of temperature on E. coli inactivation rate. Using this correlation, the time - temperature - E. coli survival relationships were derived. Besides E. coli inactivation, impacts of temperature on biogas production, methane content, pH change, ORP, and solid reduction were also studied. At higher temperatures, biogas production and methane content was greater than that at low temperatures. While at thermophilic temperature pH was increased, at mesophilic and moderate temperatures pH were reduced over the incubation period. These results can be used to understand pathogen inactivation during anaerobic digestion of dairy manure, and impacts of temperatures on performance of anaerobic digesters treating dairy manure

Assessing Linkages between E. coli Levels in Streambed Sediment and Overlying Water in an Agricultural Watershed in Iowa during the First Heavy Rain Event of the Season

This study involved field observations in Squaw Creek watershed, located in central Iowa, to investigate the impact of a heavy rain event (rainfall of 71 mm in 24 h) on E. coli levels in the streambed sediment and overlying water. We assessed relationships between streamflow and E. coli and nutrient levels in the water column and streambed sediment. The results showed that during a heavy rain event, E. coli levels in the water column varied considerably, ranging from 360 to 37,553 CFU per 100 mL with a mean of 7,598 CFU per 100 mL. Elevated streamflow resulted in greater levels of E. coli in the water column. Streambed sediment E. coli levels ranged from 896 to 6,577 CFU per 100 g with a mean of 3,355 CFU per 100 g. Regression analysis found exponential relationships between streamflow and E. coli levels in the water column (R2 = 0.56) and between streamflow and E. coli levels in the streambed sediment (R2 = 0.45). R2 values of the exponential relationship between streamflow and water column E. coli levels increased considerably when regressions for the rising and falling limbs of the hydrograph were performed separately (R2 = 0.64 and 0.94, respectively). The exponential relationship between total suspended solids (TSS) and water column E. coli levels yielded an R2 of 0.38, while TSS and streamflow yielded an exponential relationship with an R2 of 0.64. The results presented here provide information on in-stream bacteria dynamics of an agricultural watershed during the first heavy rain of the season. We anticipate that the results will improve the understanding of in-stream E. coli transport during rain events and provide insight for policy makers to allocate E. coli loads in impaired water bodies

Growth Performance and Economic Analysis of Indian Major Carps and Tilapia in Rainwater Ponds

Enhancing water resources is crucially important for improving food production in rainfed regions. The income of rural people in these regions is mainly tied with water availability. One option is disseminating rainwater harvesting for conserving rainwater and utilizing it for food production. Here we propose a rainwater harvesting method, which helps to conserve rainwater in the rainy season, provide water storage for rearing fish and facilitate supplemental irrigation to crops in the dry season. To verify the suitability of rainwater harvesting approach for improving food production and rural income, here we conducted a field study, which involved designing rainwater harvesting ponds (lined and unlined), storing rainwater and water recycling for irrigating crops. The growth of Catla catla, Labeo rohita, Cirrhinus mrigala, and tilapia in lined and unlined rainwater harvesting ponds was assessed and the resulting benefits were calculated under various scenarios. Water quality measurements showed the suitability of water stored in both rainwater harvesting ponds for fish culture. The Specific Growth Rates (SGR) of all the species in the lined ponds were greater than the unlined ponds except SGR of C. mrigala. Results show that the fish culture in the ponds improved the annual net benefit of rainwater harvesting systems. Forestimating Internal Rate of Return (IRR) and Net Present Value (NPV), the cost and benefits of the rice-fish integration was inflated using Consumer Price Index (CPI) data of 2001-2002 and 2011-2012. Unlined and lined ponds with fish culture produced annual net benefits of 118 and 188% of that without fish culture. The IRR in unlined and lined pond rainwater harvesting systems without fish rearing were 9.5 and 9.0%, while with fish culture these values increased to 13 and 26%, respectively. We anticipate that the research presented here demonstrates the potential benefits of the rainwater harvesting system and will enhance water resources in rainfed regions

A New Model for Simulating Supplemental Irrigation and the Hydro-Economic Potential of a Rainwater Harvesting System in Humid Subtropical Climates

Here we have developed a new model to simulate supplemental irrigation and the hydro-economic potential of a rainwater harvesting system in rainfed agricultural areas. Using the model, soil moisture in rainfed crop land, supplemental irrigation requirements, rainwater storage in an on-farm reservoir (OFR) system, and surface and ground water availability were predicted. In an irrigated system, an OFR was used to harvest rainwater during the rainy season, and stored water was applied to cropland as supplemental irrigation (SI). An economic analysis was performed to calculate the benefits due to an OFR irrigation system, and gains from increased crop yield and downstream water availability in the irrigated OFR system were compared with rainfed system (i.e. no OFR). In addition, we calculated the impacts of dry and wet seasons on total value gains (grain and water gains) for irrigated and rainfed conditions and performed a sensitivity analysis to quantify the impacts of model input parameters on total value gains. Analyses showed that the OFR system can produce crop yields three times greater than rainfed agriculture. During a water stress season, the total water use in the irrigated system was 65 % greater than for the rainfed system. Water use efficiency of the irrigated system was 82 % higher than for the rainfed system. In a dry season, the total value gains due to increased crop yield by supplemental irrigation and downstream water availability of the irrigated system were 74 % greater than for the rainfed system, while in a wet season the total value gain of the irrigated system was 14 % greater than for the rainfed system. A precipitation scenario analysis of wet and dry seasons indicated that the benefits of a rainwater harvesting system can be considerably greater in dry seasons than wet seasons

Respiration rate and volume measurements using wearable strain sensors.

Current methods for continuous respiration monitoring such as respiratory inductive or optoelectronic plethysmography are limited to clinical or research settings; most wearable systems reported only measures respiration rate. Here we introduce a wearable sensor capable of simultaneously measuring both respiration rate and volume with high fidelity. Our disposable respiration sensor with a Band-Aid© like formfactor can measure both respiration rate and volume by simply measuring the local strain of the ribcage and abdomen during breathing. We demonstrate that both metrics are highly correlated to measurements from a medical grade continuous spirometer on participants at rest. Additionally, we also show that the system is capable of detecting respiration under various ambulatory conditions. Because these low-powered piezo-resistive sensors can be integrated with wireless Bluetooth units, they can be useful in monitoring patients with chronic respiratory diseases in everyday settings

A neighborhood statistics model for predicting stream pathogen indicator levels

Because elevated levels of water-borne Escherichia coli in streams are a leading cause of water quality impairments in the U.S., water-quality managers need tools for predicting aqueous E. coli levels. Presently, E. coli levels may be predicted using complex mechanistic models that have a high degree of unchecked uncertainty or simpler statistical models. To assess spatio-temporal patterns of instream E. coli levels, herein we measured E. coli, a pathogen indicator, at 16 sites (at four different times) within the Squaw Creek watershed, Iowa, and subsequently, the Markov Random Field model was exploited to develop a neighborhood statistics model for predicting instream E. coli levels. Two observed covariates, local water temperature (degrees Celsius) and mean cross-sectional depth (meters), were used as inputs to the model. Predictions of E. coli levels in the water column were compared with independent observational data collected from 16 in-stream locations. The results revealed that spatio-temporal averages of predicted and observed E. coli levels were extremely close. Approximately 66 % of individual predicted E. coli concentrations were within a factor of 2 of the observed values. In only one event, the difference between prediction and observation was beyond one order of magnitude. The mean of all predicted values at 16 locations was approximately 1 % higher than the mean of the observed values. The approach presented here will be useful while assessing instream contaminations such as pathogen/pathogen indicator levels at the watershed scale

Rpp1 encodes a ULP1-NBS-LRR protein that controls immunity to Phakopsora pachyrhizi in soybean

Phakopsora pachyrhizi is the causal agent of Asian soybean rust. Susceptible soybean plants infected by virulent isolates of P. pachyrhizi are characterized by tan-colored lesions and erumpent uredinia on the leaf surface. Germplasm screening and genetic analyses have led to the identification of seven loci, Rpp1 – Rpp7, that provide varying degrees of resistance to P. pachyrhizi (Rpp). Two genes, Rpp1 and Rpp1b, map to the same region on soybean chromosome 18. Rpp1 is unique among the Rpp genes in that it confers an immune response (IR) to avirulent P. pachyrhizi isolates. The IR is characterized by a lack of visible symptoms, whereas resistance provided by Rpp1b – Rpp7 results in red-brown foliar lesions. Rpp1 maps to a region spanning approximately 150 Kb on chromosome 18 between markers Sct_187 and Sat_064 in L85-2378 (Rpp1), an isoline developed from Williams 82 and PI 200492 (Rpp1). To identify Rpp1, we constructed a bacterial artificial chromosome (BAC) library from soybean accession PI 200492. Sequencing of the Rpp1 locus identified three homologous nucleotide binding site-leucine rich repeat (NBS-LRR) candidate resistance genes between Sct_187 and Sat_064. Each candidate gene is also predicted to encode an N-terminal ubiquitin-like protease 1 (ULP1) domain. Co-silencing of the Rpp1 candidates abrogated the immune response in the Rpp1 resistant soybean accession PI 200492, indicating that Rpp1 is a ULP1-NBS-LRR protein and plays a key role in the IR