Vehicle detection is a very important aspect of computer vision application to aerial and satellite imagery, facilitating activities such as instance counting, velocity estimation, traffic ...predictions, etc. The feasibility of accurate vehicle detection often depends on limited training datasets, requiring a lot of manual work in collection and annotation tasks. Furthermore, there are no known publicly available datasets. Our aim was to construct a pipeline for synthetic dataset generation from aerial imagery and 3D models in Blender software. The dataset generation pipeline consists of seven steps and results in a wished number of images with bounding boxes in YOLO and coco formats. This synthetic dataset has been produced following the steps described in this pipeline. It consists of 5000 2048 × 2048 images with cars inserted into the roads and highways at the images without cars from all over the world. We believe that this dataset and the respective pipeline might be of great importance for vehicle detection, facilitating the customizability of the models to specific needs and context.
Real-time monitoring of crop responses to environmental deviations represents a new avenue for applications of remote and proximal sensing. Combining the high-throughput devices with novel machine ...learning (ML) approaches shows promise in the monitoring of agricultural production. The 3 × 2 multispectral arrays with responses at 610 and 680 nm (red), 730 and 760 nm (red-edge) and 810 and 860 nm (infrared) spectra were used to assess the occurrence of leaf rolling (LR) in 545 experimental maize plots measured four times for calibration dataset (n = 2180) and 145 plots measured once for external validation. Multispectral reads were used to calculate 15 simple normalized vegetation indices. Four ML algorithms were assessed: single and multilayer perceptron (SLP and MLP), convolutional neural network (CNN) and support vector machines (SVM) in three validation procedures, which were stratified cross-validation, random subset validation and validation with external dataset. Leaf rolling occurrence caused visible changes in spectral responses and calculated vegetation indexes. All algorithms showed good performance metrics in stratified cross-validation (accuracy >80%). SLP was the least efficient in predictions with external datasets, while MLP, CNN and SVM showed comparable performance. Combining ML with multispectral sensing shows promise in transition towards agriculture based on data-driven decisions especially considering the novel Internet of Things (IoT) avenues.
The paper evaluates the usability of remote satellite-based and proximal ground-based agrometeorological data sources for precision agriculture and crop production in Croatia. The compared ...agrometeorological datasets stem from the open-access data sources Copernicus CDS and the Agri4Cast portal, and commercial in situ agrometeorological stations (PinovaMeteo) which monitor environmental parameters relevant to the physiological state of crops. The study compares relevant parameters for 10 different locations in Croatia for three consecutive years (2019, 2020, and 2021) to investigate whether model-based data from ERA5-Land and Agri4Cast are well-correlated with ground measurements from independent in situ stations (PinovaMeteo) for specific agrometeorological parameters (air and soil temperature, and precipitation). Our results indicate the following: both the ERA5-Land and Agri4Cast datasets show mostly strong positive correlations with ground observations for air temperature, modest correlations for soil temperature, but modest or even low correlations for precipitation. Analysis of the residuals indicates higher overall residual values, especially in areas with complex topography and near large bodies of water or the sea, and deviations of residuals that may limit the usability of satellite- and model-based data for decision-making in agriculture.
Southeast Europe (SEE) is a very important maize-growing region, comparable to the Corn belt region of the United States, with similar dent germplasm (dent by dent hybrids). Historically, this region ...has undergone several genetic material swaps, following the trends in the US, with one of the most significant swaps related to US aid programs after WWII. The imported accessions used to make double-cross hybrids were also mixed with previously adapted germplasm originating from several more distant OPVs, supporting the transition to single cross-breeding. Many of these materials were deposited at the Maize Gene Bank of the Maize Research Institute Zemun Polje (MRIZP) between the 1960s and 1980s. A part of this Gene Bank (572 inbreds) was genotyped with Affymetrix Axiom Maize Genotyping Array with 616,201 polymorphic variants. Data were merged with two other genotyping datasets with mostly European flint (TUM dataset) and dent (DROPS dataset) germplasm. The final pan-European dataset consisted of 974 inbreds and 460,243 markers. Admixture analysis showed seven ancestral populations representing European flint, B73/B14, Lancaster, B37, Wf9/Oh07, A374, and Iodent pools. Subpanel of inbreds with SEE origin showed a lack of Iodent germplasm, marking its historical context. Several signatures of selection were identified at chromosomes 1, 3, 6, 7, 8, 9, and 10. The regions under selection were mined for protein-coding genes and were used for gene ontology (GO) analysis, showing a highly significant overrepresentation of genes involved in response to stress. Our results suggest the accumulation of favorable allelic diversity, especially in the context of changing climate in the genetic resources of SEE.
Industrial hemp is a fast-growing, short-day plant, characterized by high biomass yields and low demands for cultivation. To manipulate growth, hemp is usually cultivated under prolonged photoperiods ...or continuous light that could cause photooxidative damage and adjustments of photosynthetic reactions. To determine the extent of changes in photosynthetic response caused by prolonged light exposure, we employed chlorophyll a fluorescence measurements accompanied with level of lipid peroxidation (TBARS) and FT-IR spectroscopy on two Cannabis cultivars. Plants were grown under white (W) and purple (P) light at different photoperiods (16/8, 20/4, and 24/0). Our results showed diverse photosynthetic reactions induced by the different light type and by the duration of light exposure in two cultivars. The most beneficial condition was the 16/8 photoperiod, regardless of the light type since it brought the most efficient physiological response and the lowest TBARS contents suggesting the lowest level of thylakoid membrane damage. These findings indicate that different efficient adaptation strategies were employed based on the type of light and the duration of photoperiod. White light, at both photoperiods, caused higher dissipation of excess light causing reduced pressure on PSI. Efficient dissipation of excess energy and formation of cyclic electron transport around PSI suggests that P20/4 initiated an efficient repair system. The P24/0 maintained functional electron transport between two photosystems suggesting a positive effect on the photosynthetic reaction despite the damage to thylakoid membranes.
BackgroundThe importance of sheep breeding in the Mediterranean part of the eastern Adriatic has a long tradition since its arrival during the Neolithic migrations. Sheep production system is ...extensive and generally carried out in traditional systems without intensive systematic breeding programmes for high uniform trait production (carcass, wool and milk yield). Therefore, eight indigenous Croatian sheep breeds from eastern Adriatic treated here as metapopulation (EAS), are generally considered as multipurpose breeds (milk, meat and wool), not specialised for a particular type of production, but known for their robustness and resistance to certain environmental conditions. Our objective was to identify genomic regions and genes that exhibit patterns of positive selection signatures, decipher their biological and productive functionality, and provide a "genomic" characterization of EAS adaptation and determine its production type.ResultsWe identified positive selection signatures in EAS using several methods based on reduced local variation, linkage disequilibrium and site frequency spectrum (eROHi, iHS, nSL and CLR). Our analyses identified numerous genomic regions and genes (e.g., desmosomal cadherin and desmoglein gene families) associated with environmental adaptation and economically important traits. Most candidate genes were related to meat/production and health/immune response traits, while some of the candidate genes discovered were important for domestication and evolutionary processes (e.g., HOXa gene family and FSIP2). These results were also confirmed by GO and QTL enrichment analysis.ConclusionsOur results contribute to a better understanding of the unique adaptive genetic architecture of EAS and define its productive type, ultimately providing a new opportunity for future breeding programmes. At the same time, the numerous genes identified will improve our understanding of ruminant (sheep) robustness and resistance in the harsh and specific Mediterranean environment.
Nitrogen (N) is one of the key inputs in maize production applied in the form of fertilizers. Nitrogen deficiency during the vegetation period leads to lower yields since N is utilized in proteins ...and enzymes that enable important biochemical processes such as photosynthesis. Nitrogen deficiency leads to specific symptoms that eventually become visible to the naked eye during vegetation. Our hypothesis was that N deficiency can be detected from maize RGB images in parametric process such as a deep neural network. The aim of the reported dataset is to optimize the usage of N in the farmer's fields and accordingly, reduce its environmental footprint. This dataset contains 1200 images of maize canopy from field trials, annotated by an expert from an agricultural institution. The field trials included three levels of N fertilization: N0 without N fertilization, N75 with 75 kg of added N fertilizer, and NFull with 136 kg of added N fertilizer. For each fertilizer level, 400 plots were created with 238 different maize genotypes, resulting in a total of 1200 plots. Images were taken with a tripod mounted DSLR camera, aperture priority set to f/8 and sensor sensitivity set to ISO400. Images were taken at a 45° angle to each plot. This dataset can be useful to both researchers, data scientists and agronomists, especially in the context of emerging technologies in precision agriculture, such as robotics, 5G networks and unmanned aerial vehicle (UAV). The dataset is one of the first publicly accessible datasets of maize canopy images under different N fertilization levels and represents a valuable public resource for development of machine learning models for in-season detection of N deficiency in maize.
Linking biochemistry and genetics of tolerance to osmotic stress is of interest for understanding plant adaptations to unfavorable conditions. The aims of this study were to investigate the ...variability in responses of panel of elite maize inbred lines to water withholding for stress-related traits through association study and to identify pathways linked to detected associations for better understanding of maize stress responses. Densely genotyped public and expired Plant Variety Protection Certificate (ex-PVP) inbred lines were planted in controlled conditions (16-h/8-h day/night, 25°C, 50% RH) in control (CO) and exposed to 10-day water withholding (WW). Traits analyzed were guaiacol peroxidase activity (GPOD), total protein content (PROT), lipid peroxidation (TBARS), hydrogen peroxide accumulation (H
2
O
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), proline accumulation (proline), and current water content (CWC). Proline accumulation was found to be influenced by H
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and TBARS signaling pathways acting as an accumulation-switching mechanism. Most of the associations detected were for proline (29.4%) and TBARS (44.1%). Gene ontology (GO) enrichment analysis showed significant enrichment in regulation of integral membrane parts and peroxisomes along with regulation of transcription and polysaccharide catabolism. Dynamic studies involving inbreds with extreme phenotypes are needed to elucidate the role of this signaling mechanism in regulation of response to water deficit.
The emerging consciousness on nano- and microplastics in our environment raises questions on how to reduce and minimize its influence on human health. PET (polyethylene terephthalate) packaging is ...gaining popularity, and many traditional products end up in such packaging (vinegar, wine, beer). Currently, it is very hard to quantify the number of particles and their exact composition, but semi-quantitative techniques such as FT-IR (Fourier Transform Infrared Spectrophotometry) can give us an insight into the chemical composition of plastic bits in foods and beverages. Nowadays, beer is packed in PET packaging, since it provides a cheaper packaging material compared to glass and since it is safe to use at public manifestations, contrary to glass bottles, while providing a reasonable barrier for gas permeation (O2 and CO2). The aim of this paper was to provide a short overview of FT-IR-detected compounds in PET-packaged beer samples. The results indicate that many compounds can be found in beer, but those that were most commonly found in our research were β-cyclodextrin and L(-)-glyceraldehyde unnatural forms, two compounds designated as plastic-related compounds.
Biofortification aims to increase selenium (Se) concentration and bioavailability in edible parts of crops such as wheat (Triticum aestivum L.), resulting in increased concentration of Se in plants ...and/or soil. Higher Se concentrations can disturb protein structure and consequently influence glutathione (GSH) metabolism in plants which can affect antioxidative and other detoxification pathways. The aim of this study was to elucidate the impact of five different concentrations of selenate and selenite (0.4, 4, 20, 40 and 400 mg kg−1) on the ascorbate-glutathione cycle in wheat shoots and roots and to determine biochemical and molecular tissue-specific responses. Content of investigated metabolites, activities of detoxification enzymes and expression of their genes depended both on the chemical form and concentration of the applied Se, as well as on the type of plant tissue. The most pronounced changes in the expression level of genes involved in GSH metabolism were visible in wheat shoots at the highest concentrations of both forms of Se. Obtained results can serve as a basis for further research on Se toxicity and detoxification mechanisms in wheat. New insights into the Se impact on GSH metabolism could contribute to the further development of biofortification strategies.
•AsA-GSH cycle has an important role in wheat response to Se.•Wheat shoots and roots showed different response to selenite and selenate.•The highest concentrations of Se caused remarkable GSH metabolism changes.•Results contribute to the further development of biofortification strategies.
