Solar drying in the vineyard: a sustainable technology for the recovery of nutrients from winery organic waste

The present study describes a pilot-scale experimental validation of a forced-convection greenhouse solar dryer, combined with a biofilter, for controlled atmospheric emissions. This set-up was applied to the dewatering of sewage sludge from a biological plant that treated process wastewater in a commercial Mediterranean winery. Experiments were performed after the harvest, from September onwards, during the peak generation of sludge. The average drying rate during the first 10 days of operation ranged from 1.17 to 2.24 kg m−2 d−1, depending on the measurement method, during which the water content of the sludge was reduced from 90% down to 67%. Biofiltration was quite inefficient against greenhouse gases (methane and dinitrous oxide), and direct emissions during the drying process were on average 57 g CO2-eq m−2 d−1. Ammonia and volatile organic compounds were removed with average efficiencies of 71% and 35%, but ammonia losses through volatilization represented less than 2% of the initial nitrogen content. The sludge was dried further during November, to the lowest possible water content of 14%. Both the intermediate and final sludge dried materials were characterized for their agronomical value as organic fertilizers.info:eu-repo/semantics/acceptedVersio

Genomic Understanding of an Infectious Brain Disease from the Desert

Rhinocladiella mackenziei accounts for the majority of fungal brain infections in the Middle East, and is restricted to the arid climate zone between Saudi Arabia and Pakistan. Neurotropic dissemination caused by this fungus has been reported in immunocompromised, but also immunocompetent individuals. If untreated, the infection is fatal. Outside of humans, the environmental niche of R. mackenziei is unknown, and the fungus has been only cultured from brain biopsies. In this paper, we describe the whole-genome resequencing of two R. mackenziei strains from patients in Saudi Arabia and Qatar. We assessed intraspecies variation and genetic signatures to uncover the genomic basis of the pathogenesis, and potential niche adaptations. We found that the duplicated genes (paralogs) are more susceptible to accumulating significant mutations. Comparative genomics with other filamentous ascomycetes revealed a diverse arsenal of genes likely engaged in pathogenicity, such as the degradation of aromatic compounds and iron acquisition. In addition, intracellular accumulation of trehalose and choline suggests possible adaptations to the conditions of an arid climate region. Specifically, protein family contractions were found, including short-chain dehydrogenase/reductase SDR, the cytochrome P450 (CYP) (E-class), and the G-protein b WD-40 repeat. Gene composition and metabolic potential indicate extremotolerance and hydrocarbon assimilation, suggesting a possible environmental habitat of oil-polluted desert soilinfo:eu-repo/semantics/publishedVersio

A review of the use of convolutional neural networks in agriculture

Deep learning (DL) constitutes a modern technique for image processing, with large potential. Having been successfully applied in various areas, it has recently also entered the domain of agriculture. In the current paper, a survey was conducted of research efforts that employ convolutional neural networks (CNN), which constitute a specific class of DL, applied to various agricultural and food production challenges. The paper examines agricultural problems under study, models employed, sources of data used and the overall precision achieved according to the performance metrics used by the authors. Convolutional neural networks are compared with other existing techniques, and the advantages and disadvantages of using CNN in agriculture are listed. Moreover, the future potential of this technique is discussed, together with the authors’ personal experiences after employing CNN to approximate a problem of identifying missing vegetation from a sugar cane plantation in Costa Rica. The overall findings indicate that CNN constitutes a promising technique with high performance in terms of precision and classification accuracy, outperforming existing commonly used image-processing techniques. However, the success of each CNN model is highly dependent on the quality of the data set used.info:eu-repo/semantics/acceptedVersio

Substrate Interactions during the Biodegradation of Benzene, Toluene, Ethylbenzene, and Xylene (BTEX) Hydrocarbons by the Fungus Cladophialophora sp. Strain T1

The soil fungus Cladophialophora sp. strain T1 (= ATCC MYA-2335) was capable of growth on a model water-soluble fraction of gasoline that contained all six BTEX components (benzene, toluene, ethylbenzene, and the xylene isomers). Benzene was not metabolized, but the alkylated benzenes (toluene, ethylbenzene, and xylenes) were degraded by a combination of assimilation and cometabolism. Toluene and ethylbenzene were used as sources of carbon and energy, whereas the xylenes were cometabolized to different extents. o-Xylene and m-xylene were converted to phthalates as end metabolites; p-xylene was not degraded in complex BTEX mixtures but, in combination with toluene, appeared to be mineralized. The metabolic profiles and the inhibitory nature of the substrate interactions indicated that toluene, ethylbenzene, and xylene were degraded at the side chain by the same monooxygenase enzyme. Our findings suggest that soil fungi could contribute significantly to bioremediation of BTEX pollution

Isolation and screening of black fungi as degraders of volatile aromatic hydrocarbons

Black fungi reported as degraders of volatile aromatic compounds were isolated from hydrocarbon-polluted sites and indoor environments. Several of the species encountered are known opportunistic pathogens or are closely related to pathogenic species causing severe mycoses, among which are neurological infections in immunocompetent individuals. Given the scale of the problem of environmental pollution and the phylogenetic relation of aromatedegrading black fungi with pathogenic siblings, it is of great interest to select strains able to mineralize these substrates efficiently without any risk for public health. Fifty-six black strains were obtained from human-made environments rich in hydrocarbons (gasoline car tanks, washing machine soap dispensers) after enrichment with some phenolic intermediates of toluene and styrene fungal metabolism. Based on ITS sequencing identification, the majority of the obtained isolates were members of the genus Exophiala

Effect of Bacillus spp. direct-fed microbial on slurry characteristics and gaseous emissions in growing pigs fed with high fibre-based diets

A 26-day trial with 18 Pietrain × (Landrace × Duroc) pigs was conducted to investigate the effect of two dose levels of a specifically selected Bacillus spp. direct-fed microbial (DFM) product, on the emission of environmentally harmful gasses (methane, ammonia and hydrogen sulphide) from manure. Pigs were assigned to one of three treatments in a randomized complete block design according to their sex and initial BW. Each treatment contained three replications with two pigs per pen. The test treatments included a Bacillus spp. DFM containing 3 × 108 colony-forming unit/g, added at a low (250 mg/kg) and high (500 mg/kg) dose to an antibiotic free high fibre-based diet, and a non-supplemented control diet. Manure from pigs fed with the supplemented diets emitted lower amounts of atmospheric contaminants. The most significant reduction was observed with low DFM supplementation, in which methane and ammonia volatilization decreased ( P40% and 50%, respectively, on fresh weight basis in relation to the control. Microbiome analysis of manure by high through put sequencing techniques on eubacterial and archaeal 16S rRNA genes highlighted the complex interactions between indigenous gut microflora and inoculated Bacillus spp. The tested Bacillus DFM could be considered as a best available technique in reducing the environmental impacts of growing pigs fed with high fibre-based diets.info:eu-repo/semantics/publishedVersio