This study investigated the effects of adding biochar (BC) on the fate of ciprofloxacin (CIP) and its related antibiotic tolerance (AT) in activated sludge. Three activated sludge reactors were established with different types of BC, derived from apple, pear, and mulberry tree, respectively, and one reactor with no BC. All reactors were exposed to an environmentally relevant level of CIP that acted as a definitive selective pressure significantly promoting AT to four representative antibiotics (CIP, ampicillin, tetracycline, and polymyxin B) by up to two orders of magnitude. While CIP removal was negligible in the reactor without BC, the BC-dosed reactors effectively removed CIP (70–95% removals) through primarily adsorption by BC and biodegradation/biosorption by biomass. The AT in the BC-added reactors was suppressed by 10–99%, compared to that without BC. The BC addition played a key role in sequestering CIP, thereby decreasing the selective pressure that enabled the proactive prevention of AT increase. 16S rRNA gene sequencing analysis showed that the BC addition alleviated the CIP-mediated toxicity to community diversity and organisms related to phosphorous removal. Machine learning modeling with random forest and support vector models using AS microbiome data collectively pinpointed Achromobacter selected by CIP and strongly associated with the AT increase in activated sludge. The identification of Achromobacter as an important AT bacteria revealed by the machine learning modeling with multiple models was also validated with a linear Pearson's correlation analysis. Overall, our study highlighted Achromobacter as a potential useful sentinel for monitoring AT occurring in the environment and suggested BC as a promising additive in wastewater treatment to improve micropollutant removal, mitigate potential AT propagation, and maintain community diversity against toxic antibiotic loadings.

A rapid and sensitive immunoassay for the simultaneous detection of imidacloprid and thiacloprid was developed by using magnetic nanoparticles (MNPs) and upconversion nanoparticles (UCNPs). The UCNPs of NaYF₄:Yb, Er and NaYF₄:Yb, Tm were synthesized and conjugated with anti-imidacloprid monoclonal antibody (mAb) and anti-thiacloprid mAb as signal labels, while the MNPs were conjugated with antigens of thiacloprid and imidacloprid as separation elements. The fluorescence intensities of Yb/Er- and Yb/Tm-doped UCNPs were detected simultaneously in 544 nm and 477 nm under the excitation of NIR light (980 nm). The amounts of mAb-conjugated UCNPs that were separated by antigen-conjugated MNPs were determined based on competitive immunoassays. Under the optimal conditions, the 50% inhibiting concentration (IC₅₀) and limit of detection (LOD, IC₁₀) were 5.80 and 0.32 ng/mL for imidacloprid and 6.45 and 0.61 ng/mL for thiacloprid, respectively. The immunoassay exhibited negligible cross-reactivity with analogs of imidacloprid and thiacloprid except imidaclothiz (86.2%). The average recoveries of imidacloprid and thiacloprid in environmental and agricultural samples, including paddy water, soil, pears, oranges, cucumbers, and wheat, ranged from 78.4 to 105.9% with relative standard deviations (RSDs) of 2.1–11.9% for imidacloprid and ranged from 82.5 to 102.3% with RSDs of 1.0–16.5% for thiacloprid. In addition, the results of the immunoassay correlated well with high-performance liquid chromatography for the detection of the authentic samples.

Chemical composition and antifungal activity of essential oils of Algerian Mentha species were studied. Chemical compositions of different Mentha species oils (Mentha rotundifolia, M. spicata, M. pulegium, and M. piperita) were investigated by capillary GC and GC/MS, and their antifungal activities were evaluated by means of paper disc diffusion method and minimum inhibitory concentration (MIC) assays. In total, 98 components from all Mentha species were identified. All oils were rich in monoterpene-oxygenated components. In addition, we reported fumigant antifungal activity of Algerian Mentha essential oils against four fungi: Botrytis cinerea, Penicillium expansum, Monilinia laxa, and M. fructigena. All oils demonstrated very good inhibition especially against B. cinerea, M. laxa, and M. fructigena. Both Monilinia fungi were extremely sensitive to all Algerian Mentha oils, which suggests that Mentha essential oils have the potential to be used as bio-pesticides to protect fruit trees, such as apple and pear trees, and provides an alternative to chemical pesticides.

Acetate- and citrate-buffered quick, easy, cheap, effective, rugged, safe (QuEChERS) pretreatment methods were evaluated for the determination of various pesticides in peaches, grapes, apples, bananas, pears, and strawberries from various regions of Greece, using LC-MS/MS. The purposes of this study were (i) to evaluate which type of QuEChERS method was the most appropriate and effective for each matrix; (ii) to apply the selected QuEChERS method for each matrix, in order to detect and quantify pesticide residues in various fruit samples using UPLC-MS/MS; (iii) to examine the concentration distribution of pesticide classes among fruit originating from various areas; and (iv) to assess pesticide concentration distribution between peel and flesh of fruit in order to evaluate the penetration of pesticide residues in the fruit flesh. Acetate-buffered QuEChERS was found to be the most suitable technique for most of the fruit matrices. According to the recovery values at two different concentration levels, peaches should preferably be treated by the citrate-buffered type, whereas grapes, bananas, apples, pears, and strawberries are best treated by the acetate-buffered version, although the differences in efficiency were small. The addition of graphitized carbon black significantly decreases the recovery of specific pesticides in all matrices except for strawberries. The majority of values do not exceed the official maximum residue levels set by the European Commission. Organophosphates proved to be the most commonly detected category along with triazines-triazoles-conazoles group and by carbamates. Apples and pears seem to be the most contaminated fruit matrices among those tested. Distribution of pesticide classes shows variations between different regions, suggesting different pesticide application practices. In the case of peaches and pears, there is an equal distribution of detected pesticides between peel and flesh, indicating penetration of contaminants into the fruit flesh.

Understanding the environmental impacts of fruit production will provide fundamental information for policy making of fruit consumption and marketing. This study aims to characterize the carbon footprints of China’s fruit production and to figure out the key greenhouse gas emissions to cut with improved orchard management. Yearly input data of materials and energy in a full life cycle from material production to fruit harvest were obtained via field visits to orchards of five typical fruit types from selected areas of China. Carbon footprint (CF) was assessed with quantifying the greenhouse gas emissions associated with the individual inputs. Farm and product CFs were respectively predicted in terms of land use and of fresh fruit yield. Additionally, product CFs scaled by fruit nutrition value (vitamin C (Vc) content) and by the economic benefit from fruit production were also evaluated. The estimated farm CF ranged from 2.9 to 12.8 t CO₂-eq ha⁻¹ across the surveyed orchards, whereas the product CF ranged from 0.07 to 0.7 kg CO₂-eq kg⁻¹ fruit. While the mean product CFs of orange and pear were significantly lower than those of apple, banana, and peach, the nutrition-scaled CF of orange (0.5 kg CO₂-eq g⁻¹ Vc on average) was significantly lower than others (3.0–5.9 kg CO₂-eq g⁻¹ Vc). The income-scaled CF of orange and pear (1.20 and 1.01 kg CO₂-eq USD⁻¹, respectively) was higher than apple, banana, and peach (0.87~0.39 kg CO₂-eq USD⁻¹). Among the inputs, synthetic nitrogen fertilizer contributed by over 50 % to the total greenhouse gas (GHG) emissions, varying among the fruit types. There were some tradeoffs in product CFs between fruit nutrition value and fruit growers’ income. Low carbon production and consumption policy and marketing mechanism should be developed to cut down carbon emissions from fruit production sector, with balancing the nutrition value, producer’s income, and climate change mitigation.

This study aimed to investigate the potential health risk associated with toxic metals in contaminated foodstuffs (fruits, vegetables, and cereals) collected from various agriculture fields present in chromite mining-affected areas of mafic and ultramafic terrains (northern Pakistan). The concentrations of Cr, Ni, Zn, Cd, and Pb were quantified in both soil and food samples. The soil samples were highly contaminated with Cr (320 mg/kg), Ni (108 mg/kg), and Cd (2.55 mg/kg), which exceeded their respective safe limits set by FAO/WHO. Heavy metal concentrations in soil were found in the order of Cr>Ni>Pb>Zn>Cd and showed significantly (p < 0.001) higher concentrations as compared to reference soil. The integrated pollution load index (PLI) value was observed greater than three indicating high level of contamination in the study area. The concentrations of Cr (1.80–6.99 mg/kg) and Cd (0.21–0.90 mg/kg) in foodstuffs exceeded their safe limits, while Zn, Pb, and Ni concentrations were observed within their safe limits. In all foodstuffs, the selected heavy metal concentrations were accumulated significantly (p < 0.001) higher as compared to the reference, while some heavy metals were observed higher but not significant like Zn in pear, persimmon, white mulberry, and date-plum; Cd in pear, fig and white mulberry; and Pb in walnut, fig, and pumpkin. The health risk assessment revealed no potential risk for both adults and children for the majority of heavy metals, except Cd, which showed health risk index (HRI) >1 for children and can pose potential health threats for local inhabitants. Graphical Abstract Heavy metals released from chromite mining lead to soil and foodstuff contamination and human health risk