A simple and low cost assay for total iron in various samples based on dispersive liquid-liquid microextraction (DLLME) coupled with digital scanning image analysis was proposed. Orthogonal experiment design was utilized to optimize the amount of extraction solvent and disperser solvent, O-phenanthroline concentration and buffer pH. Under the optimum conditions, the calibration curve was linear over the range of 0.047–1.0μgmL−1 (R2>0.99) of iron. The limit of detection (LOD) for iron was 14.1μgL−1 and limit of quantification (LOQ) was 46.5μgL−1. The relative standard deviations for seven replicate determinations of 0.5μgmL−1 of iron was 3.75%. The method was successfully applied for analysis of total iron in water and food samples without using any spectral instrument and it could have a potential industrial impact in developing fast and portable devices to analyze the iron content in water and certain foods.

The heat-treated water-soluble molecules of a food-related protein, bovine serum albumin, were characterized by using size-exclusion chromatography combined with small-angle X-ray scattering measurement. Fractal analysis of the scattering data revealed that the heat-treated water-soluble species have a rod-like structural character (fractal dimension is 1). The scattering data also showed that the radius of gyration and the molecular weight of the heat-treated water-soluble aggregates are 14-15 nm and 0.98-2.3 million, respectively. Characterization of food-related biopolymers using the scattering method will be useful for the development of food processing technologies.

The mobile Food Record (mFR) is an image-based dietary assessment method for mobile devices. The study primary aim was to test the accuracy of the mFR by comparing reported energy intake (rEI) to total energy expenditure (TEE) using the doubly labeled water (DLW) method. Usability of the mFR was assessed by questionnaires before and after the study. Participants were 45 community dwelling men and women, 21–65 years. They were provided pack-out meals and snacks and encouraged to supplement with usual foods and beverages not provided. After being dosed with DLW, participants were instructed to record all eating occasions over a 7.5 days period using the mFR. Three trained analysts estimated rEI from the images sent to a secure server. rEI and TEE correlated significantly (Spearman correlation coefficient of 0.58, p < 0.0001). The mean percentage of underreporting below the lower 95% confidence interval of the ratio of rEI to TEE was 12% for men (standard deviation (SD) ± 11%) and 10% for women (SD ± 10%). The results demonstrate the accuracy of the mFR is comparable to traditional dietary records and other image-based methods. No systematic biases could be found. The mFR was received well by the participants and usability was rated as easy.

International audience

High volumes of flowback and produced water are generated everyday as a byproduct of hydraulic fracturing operations and shale gas developments across the United States. Since most shale gas developments are located in semi-arid to arid U.S. regions close to agricultural production, there are many opportunities for reusing these waters as potential alternatives or supplements to fresh water resources for irrigation activities. However, the impacts of high salinity and total organic content of these types of water on crop physiological parameters and plant growth needs to be investigated to determine their utility and feasibility. The aim of the present study was to evaluate the response of switchgrass and rapeseed to treated produced water as an irrigation water source. In this greenhouse study, the influence of produced water at four total organic carbon (TOC) concentrations [1.22, 38.3, 232.2 and 1352.4mg/l] and three total dissolved solids (TDS) levels [400,3,500, and 21,000mg/l] on rapeseed (Brassica napus L.) and switchgrass (Panicum virgatum L.), two relatively salt-tolerant, non-food, biofuel crops, was studied. Seedling emergence, biomass yield, plant height, leaf electrolyte leakage, and plant uptake were evaluated. Irrigation water with the highest salinity and TOC concentration resulted in significantly lower growth health and physiological characteristics of both crop species. The organic content of the produced water had a negative impact on biomass yield and physiological parameters of both species. The results of this study could be valuable for regulators and stakeholders in development of treatment standards in which organic matter should be removed to less than 50mg/l to keep leaf EL (cell damage) to less than 50% and a TOC concentration of less than 5mg/l required to keep a sustainable biomass production rate.

The relationship between the energy-food-water nexus and the climate is non-linear, multi-sectoral and time sensitive, incorporating aspects of complexity and risk in climate related decision-making. Current methods of analysis were not built to represent such a complex system and are insufficiently equipped to capture and understand positive and negative externalities generated by the interactions among different stakeholders involved in the energy-food-water nexus. Potential amplification effects, time delays and path dependency of climate policies are also inadequately represented. This paper seeks to explore how knowledge co-production can help identify opportunities for building more effective, sustainable, inclusive and legitimate decision making processes on climate change. This would enable more resilient responses to climate risks impacting the nexus while increasing transparency, communication and trust among key actors. We do so by proposing the operationalization of an interdisciplinary approach of analysis applying the novel methodology developed in Howarth and Monasterolo (2016). Through a bottom-up, participative approach, we present results of five themed workshops organized in the UK (focusing on: shocks and hazards, infrastructure, local economy, governance and governments, finance and insurance) featuring 78 stakeholders from academia, government and industry. We present participant’s perceptions of opportunities that can emerge from climate and weather shocks across the energy-food-water nexus. We explore opportunities offered by the development and deployment of a transdisciplinary approach of analysis within the nexus boundaries and we analyse their implications. Our analysis contributes to the current debate on how to shape global and local responses to climate change by reflecting on lessons learnt and best practice from cross-stakeholder and cross-sectorial engagement. In so doing, it helps inform a new generation of complex systems models to analyse climate change impact on the food-water-energy nexus

The mobile Food Record (mFR) is an image-based dietary assessment method for mobile devices. The study primary aim was to test the accuracy of the mFR by comparing reported energy intake (rEI) to total energy expenditure (TEE) using the doubly labeled water (DLW) method. Usability of the mFR was assessed by questionnaires before and after the study. Participants were 45 community dwelling men and women, 21–65 years. They were provided pack-out meals and snacks and encouraged to supplement with usual foods and beverages not provided. After being dosed with DLW, participants were instructed to record all eating occasions over a 7.5 days period using the mFR. Three trained analysts estimated rEI from the images sent to a secure server. rEI and TEE correlated significantly (Spearman correlation coefficient of 0.58, p &lt: 0.0001). The mean percentage of underreporting below the lower 95% confidence interval of the ratio of rEI to TEE was 12% for men (standard deviation (SD) ± 11%) and 10% for women (SD ± 10%). The results demonstrate the accuracy of the mFR is comparable to traditional dietary records and other image-based methods. No systematic biases could be found. The mFR was received well by the participants and usability was rated as easy.

A 16‐day experiment was designed to find the best combination of water temperature (27, 30, 33°C) and daily duration of food availability (12, 18, 24 h) for larval tench (Tinca tinca) growth and survival. Larvae with an initial mean size of 5.7 mm total length (TL) and 0.7 mg wet body weight (BW) were stocked at 15 L⁻¹. Larvae were fed in excess with live Artemia nauplii with the period of food availability lasting 12, 18 or 24 h daily. The largest final larval size was recorded at 27 and 30°C in groups fed for 24 h a day (17.7 and 17.9 mm TL, 76.1 and 77.7 mg BW, respectively). The combination of the highest temperature and the longest daily food availability was the only set of conditions under which final larval survival was affected (95.4% survival; 98.7–99.9% under all other conditions). The combination of water temperature of about 28.6°C and continuous food availability is recommended as the optimum combination for rearing T. tinca larvae under controlled conditions. Providing continuous food supply to fish larvae under aquaculture conditions was also advantageous in helping to mitigate the effects of slower growth relative to developmental progress, which can occur at high water temperatures. However, should one wish to limit the daily feeding period to 12 h per day, the use of a water temperature between 27.4 and 27.9°C would be the best solution.

The U.S. Food and Drug Administration (FDA) has defined standards for the microbial quality of agricultural surface water used for irrigation. According to the FDA produce safety rule (PSR), a microbial water quality profile requires analysis of a minimum of 20 samples for Escherichia coli over 2 to 4 years. The geometric mean (GM) level of E. coli should not exceed 126 CFU/100 mL, and the statistical threshold value (STV) should not exceed 410 CFU/100 mL. The water quality profile should be updated by analysis of a minimum of five samples per year. We used an extensive set of data on levels of E. coli and other fecal indicator organisms, the presence or absence of Salmonella, and physicochemical parameters in six agricultural irrigation ponds in West Central Florida to evaluate the empirical and theoretical basis of this PSR. We found highly variable log-transformed E. coli levels, with standard deviations exceeding those assumed in the PSR by up to threefold. Lognormal distributions provided an acceptable fit to the data in most cases but may underestimate extreme levels. Replacing censored data with the detection limit of the microbial tests underestimated the true variability, leading to biased estimates of GM and STV. Maximum likelihood estimation using truncated lognormal distributions is recommended. Twenty samples are not sufficient to characterize the bacteriological quality of irrigation ponds, and a rolling data set of five samples per year used to update GM and STV values results in highly uncertain results and delays in detecting a shift in water quality. In these ponds, E. coli was an adequate predictor of the presence of Salmonella in 150-mL samples, and turbidity was a second significant variable. The variability in levels of E. coli in agricultural water was higher than that anticipated when the PSR was finalized, and more detailed information based on mechanistic modeling is necessary to develop targeted risk management strategies.

The relationship between food-energy-water resources and agricultural sustainability has got a significant policy attraction that generally in favor of livelihood of the poor, which is largely affected by climate change, food security challenges, poor access of water resources, and less access of electricity. These challenges generally faced by less developing countries, while Sub-Saharan African (SSA) countries has no exemption to escape out from this food-water-energy poverty nexus due to inadequate socio-economic and environmental action programs of sustainable development. This study examined the dynamic nexus between agricultural sustainability and food-energy-water poverty in a panel of selected SSA countries over the period of 1980–2013. The study used pooled least squares regression, pooled fixed effects, and pooled random effects regression techniques to absorb country-specific-time-variant shocks. The Hausman (1978) test results reveal that country-specific shocks influence the food-energy-water poverty model; therefore, the fixed effects regression results are consider a better fit model than that of the pooled random effect model. The overall results conclude that agricultural value added, cereal yields and forest area significantly decreases food-energy-water poverty nexus, leading to higher economic growth and price levels at the cost of environmental degradation. In general, agricultural sustainability is the prerequisite for reducing food-energy-water poverty.