Stability indicating liquid chromatographic method for determination of lamivudine and tenofovir disoproxil fumarate in fixed dose combination formulations

This study describes the development and validation of a stability indicating high performance liquid chromatographic method for the analysis of lamivudine and tenofovir disoproxil fumarate and their degradants. The method uses a Reprosil®-pur basic C18 column (250 mm × 4.6 mm, 5 μm) maintained at 30°C, methanol and a mixture of buffers (2.3 g/L ammonium dihydrogen phosphate and 1.32 g/L of diammonium hydrogen phosphate, pH 3.9) for gradient elution at a flow rate of 1.0 mL/min, and UV detection at 270 nm. Good separation of lamivudine and tenofovir disoproxil fumarate and their potential impurities was achieved. The stability indicating ability of the developed method was validated by subjecting both active ingredients to hydrolytic and oxidative stress conditions and separating the degradation products from their respective intact drugs. The calibration curve was linear over the 80-120 μg/mL concentration range for both active ingredients with r2> 0.99. A recovery rate of 99.8 % for lamivudine and 99.3 % for tenofovir disoproxil fumarate confirmed the accuracy of the method for the simultaneous determination of both drugs in the fixed-dose combination.Keywords: Stability indicating liquid chromatography, lamivudine, tenofovir, validatio

Projecting the Contribution of Provitamin A Maize Biofortification and Other Nutrition Interventions to the Nutritional Adequacy and Cost of Diets in Rural Zimbabwe

Background Evidence of the effectiveness of biofortified maize with higher provitamin A (PVA) to address vitamin A deficiency in rural Africa remains scant. Objectives This study projects the impact of adopting PVA maize for a diversity of households in an area typical of rural Zimbabwe and models the cost and composition of diets adequate in vitamin A. Methods Household-level weighed food records were generated from 30 rural households during a week in April and November 2021. Weekly household intakes were calculated, as well as indicative costs of diets using data from market surveys. The impact of PVA maize adoption was modeled assuming all maize products contained observed vitamin A concentrations. The composition and cost of the least expensive indicative diets adequate in vitamin A were calculated using linear programming. Results Very few households would reach adequate intake of vitamin A with the consumption of PVA maize. However, from a current situation of 33%, 50%–70% of households were projected to reach ≤50% of their requirements (the target of PVA), even with the modest vitamin A concentrations achieved on-farm (mean of 28.3 μg RAE per 100 g). This proportion would increase if higher concentrations recorded on-station were achieved. The estimated daily costs of current diets (mean ± standard deviation) were USD 1.43 ± 0.59 in the wet season and USD 0.96 ± 0.40 in the dry season. By comparison, optimization models suggest that diets adequate in vitamin A could be achieved at daily costs of USD 0.97 and USD 0.79 in the wet and dry seasons, respectively. Conclusions The adoption of PVA maize would bring a substantial improvement in vitamin A intake in rural Zimbabwe but should be combined with other interventions (e.g., diet diversification) to fully address vitamin A deficienc

Predicting the growth of lettuce from soil infrared reflectance spectra: the potential for crop management

How well could one predict the growth of a leafy crop from reflectance spectra from the soil and how might a grower manage the crop in the light of those predictions? Two fields in the Cambridgeshire Fens in eastern England where farmers grow lettuce commercially were studied. Topsoil was sampled and analysed for various nutrients, particle-size distribution, and organic carbon concentration. Crop measurements (lettuce diameter) were derived by photogrammetry. Reflectance spectra were obtained in the laboratory from the soil in the near- and mid-infrared ranges, and these were used to predict crop performance by partial least squares regression (PLSR). Individual soil properties were also predicted from the spectra by PLSR. These estimated soil properties were used to predict lettuce diameter with a linear model (LM) and a linear mixed model (LMM): considering differences between lettuce varieties and the spatial correlation between data points. The PLSR predictions of the soil properties and lettuce diameter were close to observed values, with the latter showing a mean squared error (MSE) of 3.90 cm2 for Field 1 and 6.87 cm2 for Field 2. Prediction of lettuce diameter from the estimated soil properties with the LMs gave somewhat poorer results than those that used the soil spectra as predictor variables (difference in MSE for Field 1: 0.69 cm2 and Field 2: 2.12 cm2). Predictions from LMMs were more precise than those from the raw spectra (by PLSR alone) with a difference in mean squared error (MSE) of 2.12 cm2 for Field 1 and of 5.10 cm2 for Field 2. All model predictions improved when the effects of variety were taken into account. Predictions from the reflectance spectra, via the estimation of soil properties, can enable growers to decide what treatments to apply to grow lettuce and how to vary their treatments within their fields to maximize the net profit from the crop

How have smallholder farmers used digital extension tools? Developer and user voices from Sub-Saharan Africa, South Asia and Southeast Asia

Digital extension tools (DETs) include phone calls, WhatsApp groups and specialised smartphone applications used for agricultural knowledge brokering. We researched processes through which DETs have (and have not) been used by farmers and other extension actors in low- and middle-income countries. We interviewed 40 DET developers across 21 countries and 101 DET users in Bihar, India. We found DET use is commonly constrained by fifteen pitfalls (unawareness of DET, inaccessible device, inaccessible electricity, inaccessible mobile network, insensitive to digital illiteracy, insensitive to illiteracy, unfamiliar language, slow to access, hard to interpret, unengaging, insensitive to user's knowledge, insensitive to priorities, insensitive to socio-economic constraints, irrelevant to farm, distrust). These pitfalls partially explain why women, less educated and less wealthy farmers often use DETs less, as well as why user-driven DETs (e.g. phone calls and chat apps) are often used more than externally-driven DETs (e.g. specialised smartphone apps). Our second key finding was that users often made - not just found - DETs useful for themselves and others. This suggests the word ‘appropriation’ conceptualises DET use more accurately and helpfully than the word ‘adoption’. Our final key finding was that developers and users advocated almost ubiquitously for involving desired users in DET provision. We synthesise these findings in a one-page framework to help funders and developers facilitate more useable, useful and positively impactful DETs. Overall, we conclude developers increase DET use by recognizing users as fellow developers – either through collaborative design or by designing adaptable DETs that create room for user innovation

Construction of a generalised farm typology to aid selection, targeting and scaling of on farm research

Farm typologies are often used to reduce the complexity in categorising diverse farming systems, particularly in sub-Saharan Africa. The resulting typologies can then be used in multiple ways including designing efficient sampling schemes that capture the diversity in smallholder farms, prescribing the selection of certain farm types to which interventions can be targeted or upscaled, or to give context into derived relationships. However, the construction of farm typologies consists of many subjective decisions that are not always obvious or evident to the end-user. By developing a generalized framework for constructing farm typologies, we clarify where these subjective decisions are and quantify the impact they have on the resulting typologies. Further, this framework has been encapsulated in the open source RShiny App: TypologyGenerator to enable users to focus on the decisions and not the underlying implementation

Liming impacts barley yield over a wide concentration range of soil exchangeable cations

Liming has widespread and significant impacts on soil processes and crop responses. The aim of this study was to describe the relationships between exchangeable cation concentrations in soil and the relative yield of spring barley. The hypothesis was that yield is restricted by the concentration of a single exchangeable cation in the soil. For simplicity, we focused on spring barley which was grown in nine years of a long-term experiment at two sites (Rothamsted and Woburn). Four liming rates were applied and in each year the relative yield (RY) and the concentrations of exchangeable cations were assessed. Liming had highly significant effects on the concentrations of most exchangeable cations, except for Cu and K. There were significant negative relationships (either linear or exponential) between the exchangeable concentrations of Mn, Cd, Cr, Al, Fe, Cu, Co, Zn and Ni in soil and soil pH. The relationships between RY and the concentrations of selected exchangeable cations (Mn, Ca and Al) were described well using log-logistic relationships. For these cations a significant site effect was probably due to fundamental differences in soil properties. At both sites the concentrations of exchangeable soil Al were excessive ([ 7.5 mg kg-1) and were most likely responsible for reduced barley yields (where RY B 0.5) with soil acidification. At Rothamsted barley yield was nonlimited (where RY C 1) at soil exchangeable Mn concentrations (up to 417 mg kg-1) greater than previously considered toxic, which requires further evaluation of critical Mn concentrations

How can existing ground-based profiling instruments improve European weather forecasts?

Observations of profiles of winds, aerosol, clouds, winds, temperature and humidity in the lowest few km of the atmosphere from networks of ceilometers, Doppler wind lidars and microwave radiometers are starting to flow in real time to forecasting centers in Europe. To realise the promise of improved predictions of hazardous weather such as flash floods, wind storms, fog and poor air quality from high-resolution mesoscale models, the forecast models must be initialized with an accurate representation of the current state of the atmosphere, but the lowest few km are hardly accessible by satellite, especially in dynamically-active conditions. We report on recent European developments in the exploitation of existing ground-based profiling instruments so that they are networked and able to send data in real-time to forecast centers. The three classes of instruments are: (i) Automatic lidars and ceilometers providing backscatter profiles of clouds, aerosols, dust, fog and volcanic ash, the last two being especially important for air traffic control; (ii) Doppler wind lidars deriving profiles of wind, turbulence, wind shear, wind-gusts and low-level jets; and (iii) Microwave radiometers estimating profiles of temperature and humidity in nearly all weather conditions. Twenty-two European countries and fifteen European National Weather Services are collaborating in the project, that involves the implementation of common operating procedures, instrument calibrations, data formats and retrieval algorithms. Currently, data from 220 ceilometers in 17 countries are being distributed in near real-time to national weather forecast centers; this should soon rise to many hundreds. The wind lidars should start delivering real time data in late 2018, and the plan is to incorporate the microwave radiometers in 2019. Initial data assimilation tests indicate a positive impact of the new data

Portable X-ray fluorescence (pXRF) calibration for analysis of nutrient concentrations and trace element contaminants in fertilisers

With the increasing popularity of local blending of fertilisers, the fertiliser industry faces issues regarding quality control and fertiliser adulteration. Another problem is the contamination of fertilisers with trace elements that have been shown to subsequently accumulate in the soil and be taken up by plants, posing a danger to the environment and human health. Conventional characterisation methods necessary to ensure the quality of fertilisers and to comply with local regulations are costly, time consuming and sometimes not even accessible. Alternatively, using a wide range of unamended and intentionally amended fertilisers this study developed empirical calibrations for a portable handheld X-ray fluorescence (pXRF) spectrometer, determined the reliability for estimating the macro and micro nutrients and evaluated the use of the pXRF for the high-throughput detection of trace element contaminants in fertilisers. The models developed using pXRF for Mg, P, S, K, Ca, Mn, Fe, Zn and Mo had R2 values greater or equal to 0.97. These models also performed well on validation, with R2 values greater or equal to 0.97 (except for Fe, R2val = 0.55) and slope values ranging from 0.81 to 1.44. A second set of models were developed with a focus on trace elements in amended fertilisers. The R2 values of calibration for Co, Ni, As, Se, Cd and Pb were greater than or equal to 0.80. At concentrations up to 1000 mg kg-1, good validation statistics were also obtained; R2 values ranged from 0.97–0.99, except in one instance. The regression coefficients of the validation also had good prediction in the range of 0–100 mg kg-1 (R2 values were from 0.78–0.99), but not as well at lower concentrations up to 20 mg kg-1 (R2 values ranged from 0.10–0.99), especially for Cd. This study has demonstrated that pXRF can measure several major (P, Ca) and micro (Mn, Fe, Cu) nutrients, as well as trace elements and potential contaminants (Cr, Ni, As) in fertilisers with high accuracy and precision. The results obtained in this study is good, especially considering that loose powders were scanned for a maximum of 90 seconds without the use of a vacuum pump