Short communication: Development of an equation for estimating methane emissions of dairy cows from milk Fourier transform mid-infrared spectra by using reference data obtained exclusively from respiration chambers

Evaluation and mitigation of enteric methane (CH₄) emissions from ruminant livestock, in particular from dairy cows, have acquired global importance for sustainable, climate-smart cattle production. Based on CH₄ reference measurements obtained with the SF₆ tracer technique to determine ruminal CH₄ production, a current equation permits evaluation of individual daily CH₄ emissions of dairy cows based on milk Fourier transform mid-infrared (FT-MIR) spectra. However, the respiration chamber (RC) technique is considered to be more accurate than SF₆ to measure CH₄ production from cattle. This study aimed to develop an equation that allows estimating CH₄ emissions of lactating cows recorded in an RC from corresponding milk FT-MIR spectra and to challenge its robustness and relevance through validation processes and its application on a milk spectral database. This would permit confirming the conclusions drawn with the existing equation based on SF₆ reference measurements regarding the potential to estimate daily CH₄ emissions of dairy cows from milk FT-MIR spectra. A total of 584 RC reference CH₄ measurements (mean ± standard deviation of 400 ± 72 g of CH₄/d) and corresponding standardized milk mid-infrared spectra were obtained from 148 individual lactating cows between 7 and 321 d in milk in 5 European countries (Germany, Switzerland, Denmark, France, and Northern Ireland). The developed equation based on RC measurements showed calibration and cross-validation coefficients of determination of 0.65 and 0.57, respectively, which is lower than those obtained earlier by the equation based on 532 SF₆ measurements (0.74 and 0.70, respectively). This means that the RC-based model is unable to explain the variability observed in the corresponding reference data as well as the SF₆-based model. The standard errors of calibration and cross-validation were lower for the RC model (43 and 47 g/d vs. 66 and 70 g/d for the SF₆ version, respectively), indicating that the model based on RC data was closer to actual values. The root mean squared error (RMSE) of calibration of 42 g/d represents only 10% of the overall daily CH₄ production, which is 23 g/d lower than the RMSE for the SF₆-based equation. During the external validation step an RMSE of 62 g/d was observed. When the RC equation was applied to a standardized spectral database of milk recordings collected in the Walloon region of Belgium between January 2012 and December 2017 (1,515,137 spectra from 132,658 lactating cows in 1,176 different herds), an average ± standard deviation of 446 ± 51 g of CH₄/d was estimated, which is consistent with the range of the values measured using both RC and SF₆ techniques. This study confirmed that milk FT-MIR spectra could be used as a potential proxy to estimate daily CH₄ emissions from dairy cows provided that the variability to predict is covered by the model.     

Biohythane production from organic waste: Recent advancements,technical bottlenecks and prospects

The availability of fossil fuels is a major factor that determines the economy of a country. However, possible exhaustion of fossil fuel deposits as well as increased pollution, and other adverse effects on the environment has prompted us to search for alternative fuels. This resulted in the development of hythane, a blend of hydrogen with methane, at concentrations of 10%–30%. The breakdown of organic substrates using sequential dark fermentation (DF) and anaerobic digestion (AD) leads to biohythane production. The quality and quantity of biohythane can be improved by altering the following aspects: selection, development, and/or genetic engineering of suitable microbial consortium; the use of cheap, appropriate substrates; improved design of bioreactors; and the implementation of two-stage fermentation system. This review focusses on the mechanism of biohythane production and the different aspects involved in increasing both its production rate and quality. A comparative study has also been done to demonstrate the superiority of biohythane over other biofuels.     

In situ monitoring of the biocatalysed partial hydrolysis of cocoa butter and palm oil fraction

Partial glycerides are widely used ingredients in confectionery products that can be produced from natural fats. In a biocatalytic partial hydrolysis of cocoa butter and palm oil fractions, a product mixture containing 1.5% monoglycerides and 5.5% diglycerides intended for the use in confectionery products was created. This study is a proof of principle that shows the feasibility of monitoring the biocatalytic partial hydrolysis of these two natural fats in situ with ATR-FTIR spectroscopy. An economic approach was utilised for calibration since partial glyceride calibration standards are costly and poorly available. The released compounds were quantified by means of chemometric modelling, and the model was validated with gas chromatography. Resulting root mean square errors were in the low per cent range. Additionally, the results indicate that distinction of the released free fatty acids is possible with ATR-FTIR spectroscopy.     

Bayesian data analysis to quantify the uncertainty of intact rock strength

One of the main difficulties in the geotechnical design process lies in dealing with uncertainty. Uncertainty is associated with natural variation of properties, and the imprecision and unpredictability caused by insufficient information on parameters or models. Probabilistic methods are normally used to quantify uncertainty. However, the frequentist approach commonly used for this purpose has some drawbacks.First, it lacks a formal framework for incorporating knowledge not represented by data. Second, it has limitations in providing a proper measure of the confidence of parameters inferred from data. The Bayesian approach offers a better framework for treating uncertainty in geotechnical design. The advantages of the Bayesian approach for uncertainty quantification are highlighted in this paper with the Bayesian regression analysis of laboratory test data to infer the intact rock strength parameters σ_(ci) and m_i used in the Hoek-Brown strength criterion. Two case examples are used to illustrate different aspects of the Bayesian methodology and to contrast the approach with a frequentist approach represented by the nonlinear least squares(NLLS) method. The paper discusses the use of a Student's t-distribution versus a normal distribution to handle outliers, the consideration of absolute versus relative residuals, and the comparison of quality of fitting results based on standard errors and Bayes factors. Uncertainty quantification with confidence and prediction intervals of the frequentist approach is compared with that based on scatter plots and bands of fitted envelopes of the Bayesian approach. Finally, the Bayesian method is extended to consider two improvements of the fitting analysis. The first is the case in which the Hoek-Brown parameter, a, is treated as a variable to improve the fitting in the triaxial region. The second is the incorporation of the uncertainty in the estimation of the direct tensile strength from Brazilian test results within the overall evaluation of the intact rock strength.     

An experimental determination of combustibility

The author describes a laboratory method for determining ignitability, rate of heat release, and total heat release as a measure of the combustibility of materials. The results may be applied to building design and designation of contents with an eye towards reducing the possibility of a major fire. Note: Professor Smith is Director of Chemical Engineering Research, Engineering Experiment Station, The Ohio State University, Columbus, Ohio.     

Long-range effect of cyanide on mercury methylation in a gold mining area in southern Ecuador

Small-scale gold mining in Portovelo-Zaruma, Southern Equador, performed by mercury amalgamation and cyanidation, yields 9-10 t of gold/annum, resulting in annual releases of around 0.65 t of inorganic mercury and 6000 t of sodium cyanide in the local river system. The release of sediments, cyanide, mercury, and other metals present in the ore such as lead, manganese and arsenic significantly reduces biodiversity downstream the processing plants and enriches metals in bottom sediments and biota. However, methylmercury concentrations in sediments downstream the mining area were recently found to be one order of magnitude lower than upstream or in small tributaries. In this study we investigated cyanide, bacterial activity in water and sediment and mercury methylation potentials in sediments along the Puyango river watershed, measured respectively by in-situ spectrophotometry and incubation with ³H-leucine and ²⁰³Hg²⁺.Free cyanide was undetectable (< 1 μg·L^− 1) upstream mining activities, reached 280 μg·L^− 1 a few km downstream the processing plants area and was still detectable about 100 km downstream. At stations with detectable free cyanide in unfiltered water, 50% of it was dissolved and 50% associated to suspended particles. Bacterial activity and mercury methylation in sediment showed a similar spatial pattern, inverse to the one found for free cyanide in water, i.e. with significant values in pristine upstream sampling points (respectively 6.4 to 22 μgC·mg wet weight^− 1·h^− 1 and 1.2 to 19% of total ²⁰³Hg·g dry weight^− 1·day^− 1) and undetectable downstream the processing plants, returning to upstream values only in the most distant downstream stations. The data suggest that free cyanide oxidation was slower than would be expected from the high water turbulence, resulting in a long-range inhibition of bacterial activity and hence mercury methylation. The important mercury fluxes resultant from mining activities raise concerns about its biomethylation in coastal areas where many mangrove areas have been converted to shrimp farming.     

Research on the Influence of the Type of Surfactant and Concentrator in Aqueous Dispersion of Pigments

This work reports tests performed to evaluate the stability of aqueous dispersions of inorganic oxide pigments with different specific surface areas, with the use of anionic and non-ionic surfactants and concentrators. Color mixtures of oxide compounds of blue, green, olive and brown with the unit cell spinel structure were used as pigments. The sodium salt of sulfosuccinic acid monoester, oxyethylenated nonylphenol and ethoxylated derivatives of lauryl alcohol, fatty alcohol and fatty amine were used as surfactants. The concentrators used were: poly(vinyl alcohol), the sodium salt of carboxymethyl cellulose as well as a water-based polyurethane oligomer. The highest dispersion efficiency was found for dispersed systems in which surfactant and concentrator were incorporated in the formula. The one containing the sodium salt of carboxymethyl cellulose or polyurethane oligomer with ethoxylated saturated fatty alcohol or fatty amine was found to be the most efficient. It was discovered that a higher dispersion efficiency corresponds to pigments with larger specific surface. The efficiency is also found to improve when the concentrator is an acrylic polymer or copolymer made up of two acrylic species. In this case, the concentrator interaction with the surfactant is more effective if the value of its boundary viscosity number is higher. This observation confirms the existence of interactions between macro-chains of the concentrator and surfactant molecules forming micelles with the pigment particles.