Find research datasets worth reusing

opencc-by-4.0Dec 2023View details →

Data from: Supervised classification of plant communities with artificial neural networks

This dataset was used to test the performance of artificial neural networks for supervised classification of plant communities, published in:Černá L. & Chytrý M. (2005) Supervised classification of plant communities with artificial neural networks. Journal of Vegetation Science 16, 407-414. https://doi.org/10.1111/j.1654-1103.2005.tb02380.xThe meaning of the individual columns (separated by semicolons) in the file is as follows (for details see the above-mentioned article):<ul><li>Plot no - unique number of the vegetation plot</li><li>Group expert - plot membership in classes 1-11 of the expert  classification</li><li>Subset expert random B - assignment of the plot to the training, selection, test or ignored data subset, using the random selection of the training (and selection) subset, for the expert classification</li><li>Subset expert dg species B - assignment of the plot to the training, selection, test or ignored data subset, using the selection of the training (and selection) subset by  diagnostic species, for the expert classification</li><li>Assignment expert random - a class assignment of the plot by the MLP classifier, when trained with the randomly selected training (and selection) subset, for expert classification</li><li>Assignment expert dg-sp - a class assignment  of the plot by the MLP classifier, when trained with the plots rich in diagnostic species contained in the training (and selection) subset, for expert classification</li><li>Group cluster - plot membership in classes 1-11 of the numerical classification</li><li>Subset cluster random - assignment of the plot to the training, selection, test or ignored data subset, using the random selection of the training (and selection) subset, for numerical classification</li><li>Subset cluster dg species - assignment of the plot to the training, selection, test or ignored data subset, using the selection of the training (and selection) subset by diagnostic species, for expert classification, for numerical classification</li><li>Assignment cluster random - class assignment of the plot by the MLP classifier, when trained with the randomly selected training (and selection) subset, for expert classification, for numerical classification</li><li>Assignment cluster dg-sp - class assignment  of the plot by the MLP classifier, when trained with the plots rich in diagnostic species contained in the training (and selection) subset, for expert classification, for numerical classification </li><li>598 species, with cover/abundance estimates on an ordinal scale of 1-9</li></ul>

Fig. 4 in New species of mirid insects and their importance for the higher classification of plant bugs

Fig. 4. Photographs (A1, A3) and drawings (A2, A4) of femoral trichobothria in mirid insect Metoisops akingbohungbei Herczek and Popov, 2014, holotype male, CEHI BB M HE 4, from the Baltic Amber (unknown locality on Baltic Sea Coast), mid-Eocene. Five mesofemoral trichobothria (A1, A2); six metafemoral trichobothria (A3, A4). Scale bars 0.1 mm.

Fig. 3 in New species of mirid insects and their importance for the higher classification of plant bugs

Fig. 3. Mirid insect Metoisops popovi Kim, Taszakowski, and Jung, sp. nov., holotype female, CNU CNUHHMF005, from the Baltic Amber (unknown locality on Baltic Sea Coast), mid-Eocene. Dorsal habitus. Arrow points to deep incision between calli (A1), lateral habitus (A2), head in dorsal view (A3), head in lateral view (A4), scutellum (A5), hindfemur with trichobothria (A6).

Fig. 2 in New species of mirid insects and their importance for the higher classification of plant bugs

Fig. 2. Mirid insect Metoisops michalskii Kim, Taszakowski, and Herczek sp. nov., holotype male, DZUS HE44-451-1-001, from the Baltic Amber Gdańsk Bay, Poland), mid-Eocene. Dorsal habitus (A1), lateral habitus (A2), head and thorax in lateral view and antennal structure (A3), abdomen and legs in lateral view (A4), hindtarsus (A5), genital segment with parameres (A6). Abbreviations: i, first antennal segment; ii, second antennal segment; iii, third antennal segment; iv, fourth antennal segment; iv-1, first subsegment of fourth antennal segment; iv-2, second subsegment of fourth antennal segment.

Fig. 1 in New species of mirid insects and their importance for the higher classification of plant bugs

Fig. 1. Baltic ambers with specimens of mirid insects. A. Metoisops michalskii Kim, Taszakowski, and Herczek sp. nov., holotype male, DZUS HE44- 451-1-001, from the Baltic Amber (Vistula Spit, Gdańsk Bay, Poland), mid-Eocene. B. Metoisops popovi Kim, Taszakowski, and Jung sp. nov., holotype female, CNU CNUHHMF005, from the Baltic Amber (unknown locality on Baltic Sea Coast), mid-Eocene.

opencc-by-4.0Jun 2022View details →

PhytoNodes for Environmental Monitoring: Stimulus Classification based on Natural Plant Signals in an Interactive Energy-efficient Bio-hybrid System

Cities worldwide are growing, putting bigger populations at risk due to urban pollution. Environmental monitoring is essential and requires a major paradigm shift. We need green and inexpensive means of measuring at high sensor densities and with high user acceptance. We propose using phytosensing: using natural living plants as sensors. In plant experiments we gather electrophysiological data with sensor nodes. We expose the plant Zamioculcas zamiifolia to five different stimuli: wind, temperature, blue light, red light, or no stimulus. Using that data we train ten different types of artificial neural networks to classify measured time series according to the respective stimulus. We achieve good accuracy and succeed in running trained classifying artificial neural networks online on the microcontroller of our small energy-efficient sensor node. To indicate later possible use cases, we showcase the system by sending a notification to a smartphone application once our continuous signal analysis detects a given stimulus.   Data repository for our paper "PhytoNodes for Environmental Monitoring: Stimulus Classification based on Natural Plant Signals in an Interactive Energy-efficient Bio-hybrid System", submitted to the GoodIT conference. Please refer to the paper for more information.   Contents of this repository <ul> <li>mu_interface: Code for our data collection plant experiments, based on Raspberry Pis and the <a href="http://cybertronica.co/?q=products/phytosensor">Cybertronica phytosensing and phytoactuating system</a>.</li> <li>raw_data: The datasets from our plant experiments for the stimuli wind, temperature, red light, blue light, and no stimulus.</li> <li>dl-4-tsc: Deep learning framework developed by <a href="https://doi.org/10.1007/s10618-019-00619-1">Fawaz et. al (Deep learning for time series classification: a review)</a> and adapted to our use case. Find the training and testing datasets in the archives folder as well as the trained classifiers in the results folder.</li> <li>classification_results.ods: Overview of the results from the deep learning framework (accuracy, precision, recall, training time).</li> <li>TFLite_Models: The trained classifiers in TensorFlow Lite Format.</li> <li>00_AI_BLE_MeasuringOnlyWind: Source code for classification on STM-based PhytoNodes (using MCDCNN two-class classifier) and Bluetooth communication. The code is written for the STM32WB55 Nucleo board and can be transferred to the dongle.</li> <li>zavrsniProjekt_iOS: Source code of the iOS app used to receive data from the STM-based PhytoNodes.</li> <li>Watchplant_application_documentation.pdf: Instructions to build and use the iOS app.</li> </ul>

dryad36/100

Plant carbohydrate-active enzymes in bamboo (Neosinocalamus affinis): identification, classification and function in lignocellulose biosynthesis in herbivore defence

Neosinocalamus affinis, a type of cluster bamboo, is a good candidate feedstock for biomass energy. In the study, we found a total of 686 genes were identified as belonging to CAZyme families in the N. affinis transcriptome, including 222 glycoside hydrolases (GHs), 288 glycosyltransferases (GTs), 64 carbohydrate esterases (CEs), 70 auxiliary activities (AAs), 37 carbohydrate binding modules (CBMs) and five polysaccharide lyases (PLs). Expression profiles revealed that several CAZyme genes were up-regulated after insect infestation, particularly the GT, GH, AA and CE family members. Lignocellulose assays showed that the contents of three components, cellulose, hemicellulose and lignin, increased after insect infestation. Our findings showed that CAZyme genes were abundant in the N. affinis transcriptome and were involved in the response to herbivory. These findings could be applied to protect bamboo against herbivores, such as the bamboo snout beetle Cyrtotrachelus buqueti, and develop low-cost chemical feedstock from bamboo.

opencc-zeroFeb 2020View details →

zenodo36/100

Additional files for Horvath et al., 2024. Detection and classification of long terminal repeat sequences in plant LTR-retrotransposons and their analysis using explainable machine learning.

Additional data for Horvath et al., 2024 (source code freeze, models, data, supplementary figures, tables and files(.

opencc-by-4.0Jun 2024View details →

dryad36/100

Plant carbohydrate-active enzymes in bamboo (Neosinocalamus affinis): identification, classification and function in lignocellulose biosynthesis in herbivore defence

Open the record for dataset details and reuse information.

publicFeb 2020View details →

opencc-zeroDec 2020View details →

Supplementary material 1 from: Bustamante RO, Alves L, Goncalves E, Duarte M, Herrera I (2020) A classification system for predicting invasiveness using climatic niche traits and global distribution models: application to alien plant species in Chile. NeoBiota 63: 127-146. https://doi.org/10.3897/neobiota.63.50049

Table S1. Exotic species located in Quadrant 1 (see Figure 3) and impacts on biodiversity, agriculture and cattle raisng

opennotspecifiedDec 2012View details →

FIGURE 1. A in A revised classification of the jumping plant-lice (Hemiptera: Psylloidea)

FIGURE 1. A schematic representation of the classification proposed including all recognised families and subfamilies of Psylloidea.

opencc-by-4.0Dec 2023View details →

Supplementary Information: CHAPTER 3 - Classification of genomic features of plant-associated bacteria using machine learning

Appendix A-  List of all bacterial genomes used in orthologous  genes clustering in the feature extraction step and in the further steps to build and test classifiers’ models. The list includes the isolation source information and the  related category for the genome classification and features selection purposes. Appendix B - Distribution of genomes by phylum, family, and genus  among the categories defined according to bacteria lifestyle association. Appendix C - Enriched orthogroups by genus according to each enrichment test (Material and Methods). Values for each test are "Y" (enriched), "N" (not enriched), or "Untested" (clusters were untested when there was insufficient phylogenetic signal, they were too small or were found in all genomes). Appendix D - Classification performance of  random forest and logistic regression techniques applied to genus-specific datasets of genomic features (orthogroups) using both matrices from gene count number and presence/absence values. Sensitivity is a measure of how well a test identifies true positives; Specificity: is a measure how well a test or model avoids false positives; Positive Predictive Value (Pos. Pred. Value): The probability that a positive prediction is correct; Negative Predictive Value (Neg. Pred. Value): The probability that a negative prediction is correct; Precision: The accuracy of positive predictions; Recall (Sensitivity): The ability to find all relevant cases; F1 Score: A combined measure of precision and recall; Prevalence: The proportion of positive cases in the total; Detection Rate: The proportion of true positive cases identified; Detection Prevalence: The proportion of positive predictions; Balanced Accuracy: An average of sensitivity and specificity;  Area Under the Curve (AUC): The overall performance of the model in distinguishing between positive and negative cases. Appendix E - Orthogroups assigned with predicted COGs as an important feature for classifying plant-associated genomes. COG categories: A - RNA processing and modification; B - Chromatin structure and dynamics; C - Energy production and conversion; D - Cell cycle control, cell division, chromosome partitioning; E - Amino acid transport and metabolism; F - Nucleotide transport and metabolism; G - Carbohydrate transport and metabolism; H - Coenzyme transport and metabolism; I - Lipid transport and metabolism; J - Translation, ribosomal structure and biogenesis; K - Transcription; L - Replication, recombination and repair; M - Cell wall/membrane/envelope biogenesis; N - Cell motility; O - Posttranslational modification, protein turnover, chaperones; P - Inorganic ion transport and metabolism; Q - Secondary metabolites biosynthesis, transport and catabolism; R - General function prediction only; S - Function unknown; T - Signal transduction mechanisms; U - Intracellular trafficking, secretion, and vesicular transport; V - Defense mechanisms; W - Extracellular structures; X - Mobilome: prophages, transposons; Y - Nuclear structure; Z - Cytoskeleton.

opennotspecifiedMar 2022View details →

FIGURE. Images of representative members of tribe Phyllantheae. (A) Flowers of Nellica maderaspatensis. (B) Pistillate flowers of Cathetus gracilis, note the unique disc covering the ovary. (C) Pistillate and staminate flowers of Cathetus glaucophyllus. (D) Staminate flowers of Nymphanthus glaucescens. (E) Fruits of Kirganelia muelleriana. (F) Fruits of Lysiandra subcrenulata. (G) Phylloclade with flowers of Phyllanthus angustifolius. (H) Flowering branchlet of Phyllanthus incrustatus, note the ornamentation on the axes. (I) Habit of Moeroris tenella. (J) Fruiting branch of Dendrophyllanthus tenuirhachis. (K) Fruits of Cicca profusa. (L) Fruiting branch of Emblica officinalis. (M) Flowering plant of Emblica urinaria. (N) Pistillate flower of Breynia disticha. (O) Staminate flower of Breynia disticha. (P) flower of Glochidion dunnianum. (Q) Staminate of Glochidion lanceolarium. (R) Dehisced capsule of Glochidion sp. showing seeds covered with a red sarcotesta. Photos: A & F by J.J. Bruhl; B & P by M.S. Nuraliev; C by T. Williams; E & K by C. Jongkind; H by B. Falcón; J by R.-Y. Yu; D, G, I, L, M, N, O, Q & R by R.W.Bouman. in A revised phylogenetic classification of tribe Phyllantheae (Phyllanthaceae)

FIGURE. Images of representative members of tribe Phyllantheae. (A) Flowers of Nellica maderaspatensis. (B) Pistillate flowers of Cathetus gracilis, note the unique disc covering the ovary. (C) Pistillate and staminate flowers of Cathetus glaucophyllus. (D) Staminate flowers of Nymphanthus glaucescens. (E) Fruits of Kirganelia muelleriana. (F) Fruits of Lysiandra subcrenulata. (G) Phylloclade with flowers of Phyllanthus angustifolius. (H) Flowering branchlet of Phyllanthus incrustatus, note the ornamentation on the axes. (I) Habit of Moeroris tenella. (J) Fruiting branch of Dendrophyllanthus tenuirhachis. (K) Fruits of Cicca profusa. (L) Fruiting branch of Emblica officinalis. (M) Flowering plant of Emblica urinaria. (N) Pistillate flower of Breynia disticha. (O) Staminate flower of Breynia disticha. (P) flower of Glochidion dunnianum. (Q) Staminate of Glochidion lanceolarium. (R) Dehisced capsule of Glochidion sp. showing seeds covered with a red sarcotesta. Photos: A & F by J.J. Bruhl; B & P by M.S. Nuraliev; C by T. Williams; E & K by C. Jongkind; H by B. Falcón; J by R.-Y. Yu; D, G, I, L, M, N, O, Q & R by R.W.Bouman.

Figure 9 in Phylogeny and classification of jumping plant lice of the subfamily Liviinae (Hemiptera: Psylloidea: Liviidae) based on molecular and morphological data

Figure 9. Male terminalia and tarsal arolium of immature Liviinae: A, G, L, Klyveria crassiflagellata (Burckhardt); B, H, Liella cf. insolita (Mifsud and Burckhardt); C, Diclidophlebia fremontiae (Klyver); D, Diclidophlebia leptonychiae Burckhardt et al.; E, Haplaphalara dahli (Rübsaamen); F, Haplaphalara irvingiae (Burckhardt et al.); I, Melanastera lucens (Burckhardt et al.); J, Psyllopsis fraxini (Linnaeus); K, Livia junci (Schrank); N, Melanastera Brazil. A, B, male proctiger, in lateral view; C–I, apex of proximal portion and distal portion(s) of aedeagus; J–N, tarsal arolium of fifth instar immature. Scales A, B = 0.05 mm; C–I = 0.05 mm; J–N, = 0.05 mm.

Figure 10 in Phylogeny and classification of jumping plant lice of the subfamily Liviinae (Hemiptera: Psylloidea: Liviidae) based on molecular and morphological data

Figure 10. Maximum likelihood (ML-mix) tree resulting from a mixture (heterotachous) model (–m GTR+H4 option in IQ TREE) based on the molecular data of the Liviidae and showing the three subfamilies Euphyllurinae, Neophyllurinae, and Liviinae, and two tribes Liviini and Paurocephalini. The numbers below the branches represent the bootstrap values of ≥50. Nodes with boostrap values of <50 are shown in interrupted lines. Light blue and yellow bars indicate the non-monophyletic genera, Diclidophlebia and Haplaphalara.

Figure 2 in Phylogeny and classification of jumping plant lice of the subfamily Liviinae (Hemiptera: Psylloidea: Liviidae) based on molecular and morphological data

Figure 2. Adult Liviinae: A, Livia junci (Schrank); B, Klyveria setinervis (Burckhardt); C, Melanastera smithi (Burckhardt et al.); D, Aphorma lichenoides (Puton); E, Camarotoscena badia Loginova. A–C, head, in dorsal view; D, E, head, in oblique lateral view, with anterior carina (D, arrow), and smooth anteriorly (E). Scales 0.1 mm.

Figure 6 in Phylogeny and classification of jumping plant lice of the subfamily Liviinae (Hemiptera: Psylloidea: Liviidae) based on molecular and morphological data

Figure 6. Hindlegs of adult Liviidae: A, Anomoterga africana (Loginova); B, Syntomoza magna (Kuwayama); C, Liella cf. insolita (Mifsud and Burckhardt); D, N, Paurocephala bifasciata Kuwayama; E, Psyllopsis fraxinicola (Foerster); F, Diclidophlebia oceanica (Crawford); G, D. excetrodendri (Li and Yang); H, D. xuani (Messi); I, Haplaphalara dahli (Rübsaamen); J, H. irvingiae (Burckhardt et al.); K, Klyveria setinervis (Burckhardt); L, Liella lanceomedia (Brown and Hodkinson); M, Melanastera lucens (Burckhardt et al.); O, Camarotoscena speciosa (Flor). A–D, metacoxa; E–N, metafemur, base left; O, apex of metafemur. Scales A–D = 0.2 mm; E–N = 0.1 mm; O = 0.05 mm.

Figure 8 in Phylogeny and classification of jumping plant lice of the subfamily Liviinae (Hemiptera: Psylloidea: Liviidae) based on molecular and morphological data

Figure 8. Wings and abdomen of Liviinae: A, D, L, Aphorma lichenoides (Puton), male; M, A. lichenoides (Puton), female; B, Diclidophlebia excetrodendri (Li and Yang); C, G, Melanastera lucens (Burckhardt et al.); E, H, Livia junci (Schrank); F, J, Liella cf. insolita (Mifsud and Burckhardt); I, Diclidophlebia oceanica (Crawford); K, Tuthillia myrcianthis Burckhardt et al.; N, D. xuani (Messi); O, Paurocephala dayak Mifsud and Burckhardt, male; P, P.dayak, female. A, reduced pterostigma; B, pterostigma basally leathery, apically membranous (separating line see arrow); C, pterostigma entirely membranous; D–G, surface of forewing membrane in cell r 1: H–J, costa of hindwing; K–P, lateral edge of first visible abdominal tergite, base left. Scales A–C = 0.1 mm; D–G = 0.1 mm; H–J = 0.2 mm; K–P = 0.1 mm.

Figure 5 in Phylogeny and classification of jumping plant lice of the subfamily Liviinae (Hemiptera: Psylloidea: Liviidae) based on molecular and morphological data

Figure 5. Mesosternum of adult Liviinae: A, Anomoterga scolopiae (Yang); B, Camarotoscena speciosa (Flor); C, Klyveria setinervis (Burckhardt); D, Livia junci (Schrank); E, Paurocephala robusta Mifsud and Burckhardt; F, Syntomoza magna (Kuwayama). Abbreviations: bas, basisternum; kat, katepisternum; pcx, precoxale; pss, pleurosternal suture; scs, sternocostal suture. Scales 0.1 mm.

Figure 7 in Phylogeny and classification of jumping plant lice of the subfamily Liviinae (Hemiptera: Psylloidea: Liviidae) based on molecular and morphological data

Figure 7. Metatibial apex of adult Liviidae: A, Strophingia cinereae Hodkinson; B, Aphorma lichenoides (Puton); C, Camarotoscena speciosa (Flor); D, Livia junci (Schrank); E, Diclidophlebia oceanica (Crawford); F, D. xuani (Messi); G, Haplaphalara dahli (Rübsaamen); H, Liella lanceomedia (Brown and Hodkinson); I, Klyveria setinervis (Burckhardt); J, Melanastera lucens (Burckhardt et al.); K, M. maculipennis (Brown and Hodkinson); L, Paurocephala sauteri Enderlein. Abbreviations: a, anterior view, l, lateral view, m, medial, p, posterior view. Scales 0.05 mm.