Search Results (7)

In agriculture, manuring offers several benefits, which include improving soil fertility, structure, water retention, and aeration; all these factors favor plant health and productivity. However, improper handling and application of manure can pose risks, such as spread of pathogens and water pollution. Mitigation of such risks requires not only proper storage and composting practices, but also compliance with correct application periods and techniques. Spaceborne Earth observation can contribute to mapping manure applications and identifying possible critical situations, yet manure detection from satellite data is still a largely open question. The aim of this research is an automated, machine learning (ML)-based approach to detecting manure application on crop fields in time sequences of spaceborne, multi-source optical Earth Observation data. In the first stage of this research, multispectral data alone was considered; a pool of different spectral indexes were analyzed to identify the ones most impacted by manure application. Increments of the selected indexes from one satellite acquisition to the next were used as features to train and test various machine learning models. Two agricultural areas—one in Spain and one in Italy—were considered. Fair levels of accuracy were achieved when training and testing were carried out in the same geographical context, whereas ML models trained on one context and tested on the other reported significantly lower—albeit still acceptable—accuracy levels. In the stage that followed, thermal data was integrated and used alongside multispectral indexes. This addition led to significant improvements in accuracy levels, despite possible thermal-to-multispectral sampling mismatch in time series. Our results appear to indicate that ML-based approaches to manuring detection from space require training on the targeted geographical context, although transfer learning can probably be leveraged and only fine-tuning training will be needed. Spaceborne thermal data, where available, should be included in the input data pool to improve the quality of the final result. The proposed method is meant as a first step towards a suite of techniques that should enable large-scale, consistent monitoring of agricultural activities to check compliance with environmental regulations and provide enhanced traceability information for food products. Full article

Satellite remote sensing is currently an established, effective, and constantly used tool and methodology for monitoring agriculture and fertilisation. At the same time, in recent years, the need for the detection of livestock manure and digestate spreading on the soil is emerging, and the development of spectral indices and classification processes based on satellite multispectral data acquisitions is growing. However, the application of such indicators is still underutilised and, given the polluting impact of livestock manure and digestate on soil, groundwater, and air, an in-depth study is needed to improve the monitoring of this practice. Additionally, this paper aims at exposing a new spectral index capable of detecting the land affected by livestock manure and digestate spreading. This indicator was created by studying the spectral response of bare soil and livestock manure and digestate, using Copernicus Sentinel-2 MSI satellite acquisitions and ancillary datasets (e.g., soil moisture, precipitation, regional thematic maps). In particular, time series of multispectral satellite acquisitions and ancillary data were analysed, covering a survey period of 13 months between February 2022 and February 2023. As no previous indications on fertilisation practices are available, the proposed approach consists of investigating a broad-spectrum area, without investigations of specific test sites. A large area of approximately 236,344 hectares covering three provinces of the Emilia-Romagna Region (Italy) was therefore examined. A series of ground truth points were also collected for assessing accuracy by filling in the confusion matrix. Based on the definition of the spectral index, a value of the latter greater than three provides the most conservative threshold for detecting livestock manure and digestate spreading with an accuracy of 62.53%. Such results are robust to variations in the spectral response of the soil. On the basis of these very encouraging results, it is considered plausible that the proposed index could improve the techniques for detecting the spreading of livestock manure and digestate on bare ground, classifying the areas themselves with a notable saving of energy compared to the current investigation methodologies directly on the ground. Full article

Livestock manure management, especially related to soil-fertilisation practice, is responsible for most of the emissions in agriculture, and in particular the ammonia emissions (NH₃), which play a key role in environmental problems, affecting water, soil and air quality. Within the digital agricultural framework, EO data contribute to agricultural-practices monitoring such as manure spreading, to mitigate pollutant emissions. This study presents a GIS-based tool on an open-source platform, developed for susceptibility estimation of sewage spreading occurrence in agricultural areas of Italy. The tool is based on the analysis of multispectral and hyperspectral satellite time series in synergy with field data and ancillary information collected from regional repositories, to produce a series of classified and prioritised spatially explicit information. Spectral analysis of satellite acquisitions enabled the identification of manure spreading with the precision of about 83%. Field campaigns from October to March were carried out to validate the spreading event. The case study demonstrates the ability of the proposed GIS-based tool in supporting the monitoring of manure spreading. Full article

While the prudent and reasonable use of veterinary antimicrobial agents in food-producing animals is necessary, researchers over the decades have shown that these antimicrobial agents can spread into the environment through livestock manure and wastewater. The analysis of the occurrence of antimicrobial compounds in soil samples is of a great importance to determine potential impacts on human and animal health and the environment. In this study, an affordable, rugged and simple analytical method has been developed for the determination of twenty-nine antimicrobial compounds from five different classes (tetracyclines, fluoro(quinolones), macrolides, sulfonamides and diaminopirimidines). Liquid–liquid extraction (LLE) with extract filtration combined with ultra-high performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) was the best strategy for the simultaneous determination of all analytes. The developed method was validated according to the Commission Implementing Regulation (EU) 2021/808. The limit of detections (LODs) ranged from 0.5 to 2.0 µg/kg, while the limit of quantitation (LOQ) was established at 1.0 to 20.0 µg/kg. The developed method was successfully applied for the determination of antimicrobial residues in one hundred and eighteen soil samples obtained from four European countries (Austria, Czech Republic, Estonia and Portugal). Doxycycline in the concentration levels of 9.07 µg/kg–20.6 µg/kg was detected in eight of the analysed samples. Samples were collected from areas where natural fertilizers (swine or cow manure) were applied. Our method can be efficiently used to monitor anti-microbial compounds in soil samples. Full article

L. monocytogenes is a zoonotic foodborne pathogen with inherent adaptability to tolerate environmental and physiological stresses, thereby causing severe disease outbreaks. Antibiotic resistant foodborne pathogens are a challenge to the food industry. A total of 18 samples were pooled from a bio-digester co-digesting swine manure/pinewood sawdust, and evaluated for the occurrence of bacterium plus total viable counts using the spread plate method. The recovered bacterial isolates were presumptively identified by growth on selective medium and confirmed by biochemical characterisation, leading to the isolation of 43 L. monocytogenes. The isolates were characterized based on their susceptibility to antibiotics via the Kirby-Bauer disc diffusion technique against a panel of 14 antibiotics. Equally, the multiple antibiotic resistance (MAR) index was calculated, and MAR phenotypes generated. The bacterial counts were between 10² and10⁴ cfu/mL. Complete susceptibility (100%) was demonstrated to ampicillin, gentamicin and sulfamethoxazole, which are the drugs of choice in the treatment of listeriosis. In addition, intermediate sensitivity occurred at 25.58% to cefotaxime, and the highest resistance (51.16%) was exhibited against nalidixic acid. The MAR index ranged from 0 to 0.71. Overall, 41.86% of the Listeria isolates displayed multidrug resistance, with 18 different MAR phenotypes, demonstrating CIP, E, C, TET, AUG, S, CTX, NA, AML, NI as the greatest MAR phenotype. It can be concluded that the isolates yielding MAR > 0.2 originated from the farm, where antibiotics had been in routine use. Therefore, strict monitoring of antibiotics use in the farm is crucial to mitigate further increase in antibiotic resistance amongst these bacterial isolates. Full article

The reuse of stabilized (under thermophilic conditions) sewage sludge and manure on agricultural soils is a common practice. The aim of this study was to evaluate the risks associated with their repeated applications on the spread of pathogenic bacteria and antibiotic resistance genes (ARGs) that encode resistance to tetracycline (tetA and tetW), sulphonamide (sul1 and sul2), erythromycin (ermB), vancomycin (vanA) and integron genetic element (intI1). The trial fields has been regularly fertilized every 3rd year since 1996 with manure (MF; 330 kg N/ha) and sewage sludge (SF; 330 kg N/ha and SF3; 990 kg N/ha). Unfertilized soil (CF) served as a control. Samples were collected at different time points: (i) right before fertilization (which was also 3 years after the last fertilization), (ii) 5 months after fertilization, and (iii) 11 months after fertilization. The relative abundance of amplicon sequence variants (ASVs) assigned to potentially pathogenic bacteria was low (0.3% and 0.25% in sludge and manure, respectively), and no association with the application of these fertilizers was found. On the other hand, our data indicate that an increased relative abundance of the ARGs sul1 and tetW was significantly associated with these fertilizer applications, and sul1 was increased in all treatments regardless of the time. It is suggested that sul1 should be monitored in organically fertilized soils to prevent its spread and possible further accumulation in crops. Full article

With the extensive use of nitrogen-based fertilizer in agriculture, ammonia emissions, especially from cattle manure, are a serious environmental threat for soil and air. The European community committed to reduce the ammonia emissions by 30% by the year 2030 compared to 2005. After a moderate initial reduction, the last report showed no further improvements in the last four years, keeping the 30% reduction a very challenging target for the next decade. In this study, the mitigation effect of different types of tannin and tannin-based adsorbent on the ammonia emission from manure was investigated. Firstly, we conducted a template study monitoring the ammonia emissions registered by addition of the tannin-based powders to a 0.1% ammonia solution and then we repeated the experiments with ready-to-spread farm-made manure slurry. The results showed that all tannin-based powders induced sensible reduction of pH and ammonia emitted. Reductions higher than 75% and 95% were registered for ammonia solution and cattle slurry, respectively, when using flavonoid-based powders. These findings are very promising considering that tannins and their derivatives will be extensively available due to the increasing interest on their exploitation for the synthesis of new-generation “green” materials. Full article