Detection of Volatile Compounds Emitted from Nasal Secretions and Serum: Towards Non-Invasive Identification of Diseased Cattle Biomarkers

Dogs' ability to detect an inflammatory immune response in cattle via olfaction

Introduction

Canine olfaction is a potential means for detection of respiratory disease in beef cattle. In a prior study, two dogs were trained to discriminate between nasal swabs from healthy cattle and cattle that developed Bovine Respiratory Disease. Dogs had some ability to identify samples from BRD-affected cattle, but results were ambiguous. The purpose of this study was to evaluate more dogs using better-controlled training and testing procedures.

Methods

Nasal and saliva swabs were collected from 96 cattle before and after administering a vaccine to induce an inflammatory immune response. Samples were stored at -80°C for up to 11 months before use, and samples from animals with an elevated body temperature at baseline were omitted. An automated olfactometer apparatus was constructed to improve blinding procedures and reduce opportunities for odor contamination. Four dogs were trained to distinguish between swabs from healthy and sickness-model cattle, including the two dogs from the previous study ("Runnels" and "Cheaps") and two inexperienced dogs ("Molokai" and "Amy"). During a seven-month training period, dogs were exposed to samples from 28 animals. Dogs were tested on 59 sets of unfamiliar samples.

Results

Performance varied among dogs (χ2 = 10.48, p = 0.02). Molokai's performance was above chance (0.73 ± 0.06, p = 0.0006), while Amy (0.44 ± 0.06, p = 0.43), Cheaps (0.53 ± 0.07, p = 0.79), and Runnels (0.56 ± 0.06, p = 0.43) did not respond correctly at a rate different from chance. Accuracy did not differ between nasal swabs (0.63 ± 0.08) and saliva swabs (0.53 ± 0.08, χ2 = 0.81, p = 0.37).

Discussion

The results of this study indicate that canine olfaction may be an effective means of detecting illness in beef cattle. However, individual dogs' aptitude for this detection task varies.

A veterinary cerumenomic assay for bovine laminitis identification

Bovine laminitis disorder results in animal welfare and economic concerns in dairy and beef farms worldwide. However, the affected metabolic pathways, pathophysiologic characteristics, and inflammatory mechanisms remain unclear, hampering the development of new diagnostics. Using cerumen (earwax) as a source of volatile metabolites (cerumenomic) that carry valuable biological information has interesting implications for veterinary medicine. Nonetheless, up to now, no applications of veterinary cerumenomic assays have been made to identify bovine laminitis. This work aims to develop a veterinary cerumenomic assay for bovine laminitis identification that is non-invasive, robust, accurate, and sensitive to detecting the metabolic disturbances in bovine volatile metabolome. Twenty earwax samples (10 from healthy/control calves and 10 from laminitis calves) were collected from Nellore cattle, followed by Headspace/Gas Chromatography-Mass Spectrometry (HS/GC-MS) analysis and biomarker selection in two multivariate approaches: semiquantitative (intensity data) and semiqualitative (binary data). Following the analysis, cerumen volatile metabolites were indicated as candidate biomarkers for identifying bovine laminitis by monitoring their intensity or occurrence. In the semiquantitative strategy, the p-cresol presented the highest diagnostic figures of merit (area under the curve: 0.845, sensitivity: 0.700, and specificity: 0.900). Regarding the binary approach, a panel combining eight variables/volatiles, with formamide being the most prominent one, showed an area under the curve, sensitivity, and specificity of 0.97, 0.81, and 0.90, respectively. In summary, this work describes the first veterinary cerumenomic assay for bovine laminitis that indicates new metabolites altered during the inflammatory condition, paving the way for developing laminitis early diagnosis by monitoring the cerumen metabolites.

Strategies for Bovine Respiratory Disease (BRD) Diagnosis and Prognosis: A Comprehensive Overview

Despite significant advances in vaccination strategies and antibiotic therapy, bovine respiratory disease (BRD) continues to be the leading disease affecting the global cattle industry. The etiology of BRD is complex, often involving multiple microbial agents, which lead to intricate interactions between the host immune system and pathogens during various beef production stages. These interactions present environmental, social, and geographical challenges. Accurate diagnosis is essential for effective disease management. Nevertheless, correct identification of BRD cases remains a daunting challenge for animal health technicians in feedlots. In response to current regulations, there is a growing interest in refining clinical diagnoses of BRD to curb the overuse of antimicrobials. This shift marks a pivotal first step toward establishing a structured diagnostic framework for this disease. This review article provides an update on recent developments and future perspectives in clinical diagnostics and prognostic techniques for BRD, assessing their benefits and limitations. The methods discussed include the evaluation of clinical signs and animal behavior, biomarker analysis, molecular diagnostics, ultrasound imaging, and prognostic modeling. While some techniques show promise as standalone diagnostics, it is likely that a multifaceted approach-leveraging a combination of these methods-will yield the most accurate diagnosis of BRD.

Using Canine Olfaction to Detect Bovine Respiratory Disease: A Pilot Study

Bovine respiratory disease (BRD) is the leading cause of morbidity and mortality in feedlot cattle and is a major welfare and economic concern. Identification of BRD-affected cattle using clinical illness scores is problematic, and speed and cost constraints limit the feasibility of many diagnostic approaches. Dogs can rapidly identify humans and animals affected by a variety of diseases based on scent. Canines' olfactory systems can distinguish between patterns of volatile organic compounds produced by diseased and healthy tissue. In this pilot study, two dogs (“Runnels” and “Cheaps”) were trained for 7 months to discriminate between nasal swabs from cattle that developed signs of BRD within 20 days of feedlot arrival and swabs from cattle that did not develop BRD signs within 3 months at the feedlot. Nasal swabs were collected during cattle processing upon arrival to the feedlot and were stored at −80°C. Dogs were presented with sets of one positive and two negative samples and were trained using positive reinforcement to hold their noses over the positive sample. The dogs performed moderately well in the final stage of training, with accuracy for Runnels of 0.817 and Cheaps of 0.647, both greater than the 0.333 expected by chance. During a double-blind detection test, dogs evaluated 123 unique and unfamiliar samples that were presented as 41 sets (3 samples per set), with both the dog handler and data recorder blinded to the positive sample location. Each dog was tested twice on each set of samples. Detection test accuracy was slightly better than chance for Cheaps at 0.451 (95% CI: 0.344–0.559) and was no better than chance for Runnels at 0.390 (95% CI: 0.285–0.496. Overall accuracy was 0.421 (95% CI: 0.345–0.496). When dogs' consensus response on each sample set was considered, accuracy was 0.537 (95% CI: 0.384–0.689). Detection accuracy also varied by sample lot. While dogs showed some ability to discriminate between BRD-affected and healthy cattle using nasal swabs, the complexity of this task suggests that more testing is needed before determining whether dogs could be effective as a screening method for BRD.

Passive breath monitoring of livestock: Using factor analysis to deconvolve the cattle shed

Respiratory and metabolic diseases in livestock cost the agriculture sector billions each year, with delayed diagnosis a key exacerbating factor. Previous studies have shown the potential for breath analysis to successfully identify incidence of disease in a range of livestock. However, these techniques typically involve animal handling, the use of nasal swabs or fixing a mask to individual animals to obtain a sample of breath. Using a cohort of 26 cattle as an example, we show how the breath of individual animals within a herd can be monitored using a passive sampling system, where no such handling is required. These benefits come at the cost of the desired breath samples unavoidably mixed with the complex cocktail of odours that are present within the cattle shed. Data were analysed using positive matrix factorisation (PMF) to identify and remove non-breath related sources of VOC. In total three breath factors were identified (endogenous-, non-endogenous breath and rumen) and seven factors related to other sources within and around the cattle shed (e.g. foodcattle feed, traffic, urine and faeces). Simulation of a respiratory disease within the herd showed that the abnormal change in breath composition were captured in the residuals of the 10 factor PMF solution, highlighting the importance of their inclusion as part of the breath fraction. Increasing the number of PMF factors to 17 saw the identification of a "diseased" factor, which coincided with the visits of the three "diseased" cattle to the breath monitor platform. This work highlights the important role that factor analysis techniques can play in analysing passive breath monitoring data.

Bovine Respiratory Syncytial Virus (BRSV) Infection Detected in Exhaled Breath Condensate of Dairy Calves by Near-Infrared Aquaphotomics

Bovine respiratory syncytial virus (BRSV) is a major contributor to respiratory disease in cattle worldwide. Traditionally, BRSV infection is detected based on non-specific clinical signs, followed by reverse transcriptase-polymerase chain reaction (RT-PCR), the results of which can take days to obtain. Near-infrared aquaphotomics evaluation based on biochemical information from biofluids has the potential to support the rapid identification of BRSV infection in the field. This study evaluated NIR spectra (n = 240) of exhaled breath condensate (EBC) from dairy calves (n = 5) undergoing a controlled infection with BRSV. Changes in the organization of the aqueous phase of EBC during the baseline (pre-infection) and infected (post-infection and clinically abnormal) stages were found in the WAMACS (water matrix coordinates) C1, C5, C9, and C11, likely associated with volatile and non-volatile compounds in EBC. The discrimination of these chemical profiles by PCA-LDA models differentiated samples collected during the baseline and infected stages with an accuracy, sensitivity, and specificity >93% in both the calibration and validation. Thus, biochemical changes occurring during BRSV infection can be detected and evaluated with NIR-aquaphotomics in EBC. These findings form the foundation for developing an innovative, non-invasive, and in-field diagnostic tool to identify BRSV infection in cattle.

Supplement Based on Fermented Milk Permeate for Feeding Newborn Calves: Influence on Blood, Growth Performance, and Faecal Parameters, including Microbiota, Volatile Compounds, and Fatty and Organic Acid Profiles

Simple Summary

Gastrointestinal infections and diarrhoea are the main health issues in young calves. The application of microbial products containing probiotics and prebiotics may lead to better management of the gut microbiome and improved calf health. After fermentation with selected lactic acid bacterial strains, milk permeate (a dairy industry by-product) contains lactic acid bacteria and prebiotics, both of which possess viable antimicrobial properties. We hypothesised that fermented milk permeate could be a prospective feed supplement for newborn calves. A 14-day experiment was conducted in which a group of newborn calves were given a supplement of milk permeate fermented with Lactobacillus uvarum LUHS245. A significantly higher count of lactic acid bacteria, a lower total count of enterobacteria, a higher species variety, and greater concentrations of both propionic acid and dry matter were found in the faeces of the calves fed with fermented milk permeate compared with a control group. Most of the fatty acids and volatile compounds in the faeces differed significantly between the two groups. The results suggest that supplementing the calves’ feed with fermented milk permeate has a positive effect on certain health parameters but no influence on blood parameters and growth performance.

Abstract

The aim of this study was to assess the effect of a feed supplement, namely milk permeate (MP) fermented with Lactobacillus uvarum LUHS245, on the newborn calves’ growth performance and blood and faecal parameters, including microbiota and volatile compound and fatty acid profiles. Ten female Holstein calves in the control group (CON group) were fed with a standard milk replacer diet and colostrum only, from day 2 to 14 of life, while 10 calves of the treated group (MP group) were fed with the same diet supplemented with 50 mL of the fermented MP. After 14 days, there were no significant differences between the groups in blood parameters, growth performance, or faecal pH. There was a significantly higher percentage of live lactic acid bacteria (by 17.02%), a lower percentage of enterobacteria (by 10.38%), a higher overall number of probiotic bacteria, a 1.7-fold higher species variety, and a higher content of dry matter in the faeces of the MP group (p < 0.05). The fatty acid and volatile compound profiles differed significantly between the groups. The results suggest that supplementing calves’ feed with fermented milk permeate has a positive effect on certain health parameters but not on blood parameters or growth performance.

Portable Electronic Nose for Analyzing the Smell of Nasal Secretions in Calves: Toward Noninvasive Diagnosis of Infectious Bronchopneumonia

The paper demonstrates a new approach to identify healthy calves (“healthy”) and naturally occurring infectious bronchopneumonia (“sick”) calves by analysis of the gaseous phase over nasal secretions using 16 piezoelectric sensors in two portable devices. Samples of nasal secretions were obtained from 50 red-motley Holstein calves aged 14–42 days. Calves were subjected to rectal temperature measurements, clinical score according to the Wisconsin respiratory scoring chart, thoracic auscultation, and radiography (Carestream DR, New York, USA). Of the 50 calves, we included samples from 40 (20 “healthy” and 20 “sick”) in the training sample. The remaining ten calves (five “healthy” and five “sick”) were included in the test sample. It was possible to divide calves into “healthy” and “sick” groups according to the output data of the sensor arrays (maximum sensor signals and calculated parameters A_i/j) using the principal component linear discriminant analysis (PCA–LDA) with an accuracy of 100%. The adequacy of the PCA–LDA model was verified on a test sample. It was found that data of sensors with films of carbon nanotubes, zirconium nitrate, hydroxyapatite, methyl orange, bromocresol green, and Triton X-100 had the most significance for dividing samples into groups. The differences in the composition of the gaseous phase over the samples of nasal secretions for such a classification could be explained by the appearance or change in the concentrations of ketones, alcohols, organic carboxylic acids, aldehydes, amines, including cyclic amines or those with a branched hydrocarbon chain.

Profiling Mannheimia haemolytica infection in dairy calves using near infrared spectroscopy (NIRS) and multivariate analysis (MVA)

Bovine respiratory disease (BRD) linked with Mannheimia haemolytica is the principal cause of pneumonia in cattle. Diagnosis of BRD traditionally relies on visual assessment, which can be untimely, insensitive, and nonspecific leading to inadequate treatment and further spread of disease. Near Infrared Spectroscopy (NIRS) is a rapid acquisition vibrational spectroscopy that can profile changes in biofluids, and when used in combination with multivariate analysis, has potential for disease diagnosis. This study characterizes the NIR spectral profile of blood plasma from dairy calves infected with M. haemolytica and validates the spectral biochemistry using standardized clinical and hematological reference parameters. Blood samples were collected for four days prior to (baseline), and 23 days after, a controlled intrabronchial challenge. NIR spectral profiles of blood plasma discriminated and predicted Baseline and Infected states of animal disease progression with accuracy, sensitivity, and specificity ≥ 90% using PCA–LDA models. These results show that physiological and biochemical changes occurring in the bloodstream of dairy calves during M. haemolytica infection are reflected in the NIR spectral profiles, demonstrating the potential of NIRS as a diagnostic and monitoring tool of BRD over time.

Transforming the Adaptation Physiology of Farm Animals through Sensors

Simple Summary

Strategy for the protection and welfare of farm animals, and the sustainable animal production is dependent on the thorough understanding of the adaptation physiology. Real-time, continuous, and precise measurement of the multi-dimensions and complex intricacies of adaptive capacity of farm animals namely the mental, behavioral, and physiological states are possible only through the sensor-based approaches. This paper critically reviews the latest sensor technologies as assessment tools for the adaptation physiology of farm animals and explores their advantages over traditional measurement methods. Digital innovation, diagnostics, genetic testing, biosensors, and wearable animal devices are important tools that enable the development of decision support farming platforms and provides the path for predicting diseases in livestock. Sensor fusion data from a multitude of biochemical, emotional, and physiological functions of the farm animals not only helps to identify the most productive animal but also allows farmers to predict which individual animal may have greater resilience to common diseases. Insights into the cost of adoption of sensor technologies on farms including computing capacity, human resources in training, and the sensor hardware are being discussed.

Abstract

Despite recent scientific advancements, there is a gap in the use of technology to measure signals, behaviors, and processes of adaptation physiology of farm animals. Sensors present exciting opportunities for sustained, real-time, non-intrusive measurement of farm animal behavioral, mental, and physiological parameters with the integration of nanotechnology and instrumentation. This paper critically reviews the sensing technology and sensor data-based models used to explore biological systems such as animal behavior, energy metabolism, epidemiology, immunity, health, and animal reproduction. The use of sensor technology to assess physiological parameters can provide tremendous benefits and tools to overcome and minimize production losses while making positive contributions to animal welfare. Of course, sensor technology is not free from challenges; these devices are at times highly sensitive and prone to damage from dirt, dust, sunlight, color, fur, feathers, and environmental forces. Rural farmers unfamiliar with the technologies must be convinced and taught to use sensor-based technologies in farming and livestock management. While there is no doubt that demand will grow for non-invasive sensor-based technologies that require minimum contact with animals and can provide remote access to data, their true success lies in the acceptance of these technologies by the livestock industry.

Details to Attend to When Managing High-Risk Cattle

This article provides insights into the management of bovine respiratory disease in high-risk cattle populations. Biocontainment strategies, records, procurement, transport, arrival/receiving management, vaccination, and treatment protocols are discussed from practical and systems-thinking perspectives regarding their impact on health in high-risk cattle. Arrival management considerations, such as facilities, nutritional management, metaphylaxis, bovine viral diarrhea virus persistent infection testing, parasite control, and castration, are also addressed. Caretaker morale and job satisfaction are suggested as important factors to consider when managing high-risk cattle. The inter-relationships of variables within the system are explored as contributing causative factors to bovine respiratory disease in high-risk cattle.

Diagnosis of Bovine Respiratory Disease in feedlot cattle using blood 1H NMR metabolomics

Current diagnosis methods for Bovine Respiratory Disease (BRD) in feedlots have a low diagnostic accuracy. The current study aimed to search for blood biomarkers of BRD using ¹H NMR metabolomics and determine their accuracy in diagnosing BRD. Animals with visual signs of BRD (n = 149) and visually healthy (non-BRD; n = 148) were sampled for blood metabolomics analysis. Lung lesions indicative of BRD were scored at slaughter. Non-targeted ¹H NMR metabolomics was used to develop predictive algorithms for disease classification using classification and regression trees. In the absence of a gold standard for BRD diagnosis, six reference diagnosis methods were used to define an animal as BRD or non-BRD. Sensitivity (Se) and specificity (Sp) were used to estimate diagnostic accuracy (Acc). Blood metabolomics demonstrated a high accuracy at diagnosing BRD when using visual signs of BRD (Acc = 0.85), however was less accurate at diagnosing BRD using rectal temperature (Acc = 0.65), lung auscultation score (Acc = 0.61) and lung lesions at slaughter as reference diagnosis methods (Acc = 0.71). Phenylalanine, lactate, hydroxybutyrate, tyrosine, citrate and leucine were identified as metabolites of importance in classifying animals as BRD or non-BRD. The blood metabolome classified BRD and non-BRD animals with high accuracy and shows potential for use as a BRD diagnosis tool.

Volatile metabolomic signatures of rabies immunization in two mesocarnivore species

Rabies is a zoonotic disease caused by infection with rabies virus, which circulates naturally in several wild carnivore and bat reservoirs in the United States (US). The most important reservoir in the US from an animal and public health perspective is the raccoon (Procyon lotor). To prevent the westward expansion of a significant raccoon rabies epizootic along the eastern seaboard, an operational control program implementing oral rabies vaccination (ORV) has existed in the US since the 1990s. Recently, two vaccine efficacy studies conducted with raccoons and striped skunks (Mephitis mephitis) provided the opportunity to determine if volatile fecal metabolites might be used to non-invasively monitor ORV programs and/or predict virus protection for these species. The volatile metabolome is a rich source of information that may significantly contribute to our understanding of disease and infection. Fecal samples were collected at multiple time points from raccoons and striped skunks subjected to oral treatment with rabies vaccine (or sham). Intramuscular challenge with a lethal dose of rabies virus was used to determine protection status at six (raccoons) and 11 (skunks) months post-vaccination. In addition to fecal samples, blood was collected at various time points to permit quantitative assessment of rabies antibody responses arising from immunization. Feces were analyzed by headspace gas chromatography with mass spectrometric detection and the chromatographic responses were grouped according to cluster analysis. Cluster scores were subjected to multivariate analyses of variance (MANOVA) to determine if fecal volatiles may hold a signal of immunization status. Multiple regression was then used to build models of the measured immune responses based on the metabolomic data. MANOVA results identified one cluster associated with protective status of skunks and one cluster associated with protective status of raccoons. Regression models demonstrated considerably greater success in predicting rabies antibody responses in both species. This is the first study to link volatile compounds with measures of adaptive immunity and provides further evidence that the volatile metabolome holds great promise for contributing to our understanding of disease and infections. The volatile metabolome may be an important resource for monitoring rabies immunization in raccoons and striped skunks.

Screening of Microbial Volatile Organic Compounds for Detection of Disease in Cattle: Development of Lab-scale Method

The primary hurdle for diagnosis of some diseases is the long incubation required to culture and confirm the presence of bacteria. The concept of using microbial VOCs as "signature markers" could provide a faster and noninvasive diagnosis. Finding biomarkers is challenging due to the specificity required in complex matrices. The objectives of this study were to (1) build/test a lab-scale platform for screening of microbial VOCs and (2) apply it to Mycobacterium avium paratuberculosis; the vaccine strain of M. bovis Bacillus Calmette-Guérin; and M. kansasii to demonstrate detection times greater those typically required for culture. SPME-GC-MS was used for sampling, sample preparation, and analyses. For objective (1), a testing platform was built for headspace sampling of bacterial cultures grown in standard culture flasks via a biosecure closed-loop circulating airflow system. For (2), results show that the suites of VOCs produced by Mycobacteria ssp. change over time and that individual strains produce different VOCs. The developed method was successful in discriminating between strains using a pooled multi-group analysis, and in timepoint-specific multi- and pair-wise comparisons. The developed testing platform can be useful for minimally invasive and biosecure collection of biomarkers associated with human, wildlife and livestock diseases for development of diagnostic point-of-care and field surveillance.

Solid-phase microextraction: An appealing alternative for the determination of endogenous substances - A review

The determination of endogenous substances is of great significance for obtaining important biotic information such as biological components, metabolic pathways and disease biomarkers in different living organisms (e.g. plants, insects, animals and humans). However, due to the complex matrix and the trace concentrations of target analytes, the sample preparation procedure is an essential step before the analytes of interest are introduced into a detection instrument. Solid-phase microextraction (SPME), an emerging sample preparation technique that integrates sampling, extraction, concentration, and sample introduction into one step, has gained wide acceptance in various research fields, including in the determination of endogenous compounds. In this review, recent developments and applications of SPME for the determination of endogenous substances over the past five years are summarized. Several aspects, including the design of SPME devices (sampling configuration and coating), applications (in vitro and in vivo sampling), and coupling with emerging instruments (comprehensive two-dimensional gas chromatography (GC × GC), ambient mass spectrometry (AMS) and surface enhanced Raman scattering (SERS)) are involved. Finally, the challenges and opportunities of SPME methods in endogenous substances analysis are also discussed.

The Proof-of-the-Concept of Application of Pelletization for Mitigation of Volatile Organic Compounds Emissions from Carbonized Refuse-Derived Fuel

Waste can be effectively reused through the production of carbonized refuse-derived fuel (CRDF) that enables further energy recovery. Developing cleaner production of CRDF requires consideration of practical issues of storage and handling. Thus, it needs to be ensured that CRDF does not pose an excessive risk to humans and the ecosystem. Very few studies indicate a wide variety of volatile organic compounds (VOCs) are present in CRDF, some of which are toxic. During handling, storage, transportation, and use of VOC-rich CRDF, workers and end-users could be exposed to emissions that could pose a health and safety hazard. Our recent study shows that CRDF densification via pelletization can increase the efficiency of storage and transportation. Thus, the following research question was identified: can pelletization mitigate VOCs emissions from CRDF during storage? Preliminary research aiming at the determination of the influence of CRDF pelletization on VOCs emission during storage was completed to address this question. The VOCs emissions from two types of CRDF: ground (loose, torrefied refuse-derived fuel (RDF)) and pelletized, were measured. Pelletization reduced the VOCs emissions potential during the four-day storage by ~86%, in comparison with ground CRDF. Mitigation of VOCs emissions from densified CRDF is feasible, and research is warranted to understand the influence of structural modification on VOCs emission kinetics, and possibilities of scaling up this solution into the practice of cleaner storage and transportation of CRDF.

Quantification of VOC Emissions from Carbonized Refuse-Derived Fuel Using Solid-Phase Microextraction and Gas Chromatography-Mass Spectrometry

In this work, for the first time, the volatile organic compound (VOC) emissions from carbonized refuse-derived fuel (CRDF) were quantified on a laboratory scale. The analyzed CRDF was generated from the torrefaction of municipal waste. Headspace solid-phase microextraction (SPME) and gas chromatography-mass spectrometry (GC-MS) was used to identify 84 VOCs, including many that are toxic, e.g., derivatives of benzene or toluene. The highest emissions were measured for nonanal, octanal, and heptanal. The top 10 most emitted VOCs contributed to almost 65% of the total emissions. The VOC mixture emitted from torrefied CRDF differed from that emitted by other types of pyrolyzed biochars, produced from different types of feedstock, and under different pyrolysis conditions. SPME was a useful technology for surveying VOC emissions. Results provide an initial database of the types and relative quantities of VOCs emitted from CRDF. This data is needed for further development of CRDF technology and comprehensive assessment of environmental impact and practical storage, transport, and potential adoption of CRDF as means of energy and resource recovery from municipal waste.