Stress Knowledge Map(SKM;https://skm.nib.si)is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical,signaling,and regulatory molecular interact...Stress Knowledge Map(SKM;https://skm.nib.si)is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical,signaling,and regulatory molecular interactions in plants:a highly curated model of plant stress signaling(PSS;543 reactions)and a large comprehensive knowledge network(488390 interactions).Both were constructed by domain experts through systematic curation of diverse literature and database resources.SKM provides a single entry point for investigations of plant stress response and related growth trade-offs,as well as interactive explorations of current knowledge.PSS is also formulated as a qualitative and quantitative model for systems biology and thus represents a starting point for a plant digital twin.Here,we describe the features of SKM and show,through two case studies,how it can be used for complex analyses,including systematic hypothesis generation and design of validation experiments,or to gain new insights into experimental observations in plant biology.展开更多
The perceived visual quality of fruits and vegetables plays a central role in the choices made by retail customers.Machine learning(ML)approaches based on image analysis have been recently proposed to overcome the poo...The perceived visual quality of fruits and vegetables plays a central role in the choices made by retail customers.Machine learning(ML)approaches based on image analysis have been recently proposed to overcome the poor efficiency and subjectivity of human visual evaluation as well as the expensiveness and destructiveness of physical and chemical methods that measure internal indicators.In this paper,we propose a ML method based on Random Forests for estimating the chlorophyll and ammonia contents(considered,in the literature,reliable indicators of product freshness)from images of fresh-cut rocket leaves.Our approach copes with specific issues raised by(i)the non-uniform distributions of ammonia and chlorophyll values and(ii)the need to provide insights into the features that produce a particular model outcome,aiming to enhance its trustworthiness.Our experiments,performed on real images of fresh-cut rocket leaves,proved that the proposed approach significantly outperforms 7 competitor methods,obtaining an improvement of the RSE results of 6.6%for the prediction of the ammonia and of 10.4%for the prediction of the chlorophyll over its best competitor.Moreover,a specific analysis of the explainability of the predictions showed that the learned models are based on reasonable features,empowering their acceptance in real-world applications.展开更多
Wallemia comprises air-and food-borne,mycotoxigenic contaminants including the halophilic W.ichthyophaga,xerotolerant W.sebi and xerophilic W.muriae.Wallemia isolates are easily overlooked and only a comparably small ...Wallemia comprises air-and food-borne,mycotoxigenic contaminants including the halophilic W.ichthyophaga,xerotolerant W.sebi and xerophilic W.muriae.Wallemia isolates are easily overlooked and only a comparably small number of strains have been deposited in culture collections so far.In order to better understand the natural distribution of Wallemia spp.and to encounter their natural habitats,we tested more than 300 low-water-activity substrates and 30 air samples from a wide geographical coverage.We isolated more than 150 new Wallemia strains.Wallemia sebi and W.muriae were isolated mostly from hypersaline water,low-water-activity foods,plant materials and indoor.Wallemia muriae is the dominant Wallemia species in the air of natural and human influenced environments in Europe.New isolates of W.ichthyophaga were obtained from hypersaline environments such as brine,salt crystals,salty foods and MgCl_(2)-rich bitterns,and from the air of hay barns in Denmark.Five halotolerant strains were recognised as a hitherto un-described species Wallemia hederae,the phylogenetic sister of the halophilic W.ichthyophaga.Wallemia spp.show in-vitro growth on media that contain the chaotropic salt MgCl_(2).Wallemia ichthyophaga can grow in liquid medium enriched with 2 M MgCl_(2).Never before has a microorganism been grown on comparably high MgCl_(2) concentrations.Tests of the activity of a wide range of extracellular enzymes in the presence of NaCl also suggested that Wallemia iswell-adapted to substrates with a reduced water activity.展开更多
基金funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement 862858(ADAPT)the Slovenian Research Agency under grant agreements 1000-15-0105,Z7-1888,J4-1777,P4-0165,N4-0199,Z4-50146,and J4-3089ELIXIR,the research infrastructure for life science data through the ELIXIR Implementation Study“Increasing plant data findability for ELIXIR and beyond”and ELIXIR-SI.We gratefully acknowledge funding from the Deutsche Forschungsgemeinschaft(DFG)to U.C.V.(INST 217/939-1 FUGG).
文摘Stress Knowledge Map(SKM;https://skm.nib.si)is a publicly available resource containing two complementary knowledge graphs that describe the current knowledge of biochemical,signaling,and regulatory molecular interactions in plants:a highly curated model of plant stress signaling(PSS;543 reactions)and a large comprehensive knowledge network(488390 interactions).Both were constructed by domain experts through systematic curation of diverse literature and database resources.SKM provides a single entry point for investigations of plant stress response and related growth trade-offs,as well as interactive explorations of current knowledge.PSS is also formulated as a qualitative and quantitative model for systems biology and thus represents a starting point for a plant digital twin.Here,we describe the features of SKM and show,through two case studies,how it can be used for complex analyses,including systematic hypothesis generation and design of validation experiments,or to gain new insights into experimental observations in plant biology.
基金supported by the project FAIR-Future AI Research(PE00000013)spoke 6–Symbiotic AI,under the NRRP MUR program funded by the NextGenerationEU and by the project Prin 2017“SUS&LOW-Sustaining low-impact practices in horticulture through non-destructive approach to provide more information on fresh produce history and quality”(grant number:201785Z5H9)from the Italian Ministry of University and Research。
文摘The perceived visual quality of fruits and vegetables plays a central role in the choices made by retail customers.Machine learning(ML)approaches based on image analysis have been recently proposed to overcome the poor efficiency and subjectivity of human visual evaluation as well as the expensiveness and destructiveness of physical and chemical methods that measure internal indicators.In this paper,we propose a ML method based on Random Forests for estimating the chlorophyll and ammonia contents(considered,in the literature,reliable indicators of product freshness)from images of fresh-cut rocket leaves.Our approach copes with specific issues raised by(i)the non-uniform distributions of ammonia and chlorophyll values and(ii)the need to provide insights into the features that produce a particular model outcome,aiming to enhance its trustworthiness.Our experiments,performed on real images of fresh-cut rocket leaves,proved that the proposed approach significantly outperforms 7 competitor methods,obtaining an improvement of the RSE results of 6.6%for the prediction of the ammonia and of 10.4%for the prediction of the chlorophyll over its best competitor.Moreover,a specific analysis of the explainability of the predictions showed that the learned models are based on reasonable features,empowering their acceptance in real-world applications.
文摘Wallemia comprises air-and food-borne,mycotoxigenic contaminants including the halophilic W.ichthyophaga,xerotolerant W.sebi and xerophilic W.muriae.Wallemia isolates are easily overlooked and only a comparably small number of strains have been deposited in culture collections so far.In order to better understand the natural distribution of Wallemia spp.and to encounter their natural habitats,we tested more than 300 low-water-activity substrates and 30 air samples from a wide geographical coverage.We isolated more than 150 new Wallemia strains.Wallemia sebi and W.muriae were isolated mostly from hypersaline water,low-water-activity foods,plant materials and indoor.Wallemia muriae is the dominant Wallemia species in the air of natural and human influenced environments in Europe.New isolates of W.ichthyophaga were obtained from hypersaline environments such as brine,salt crystals,salty foods and MgCl_(2)-rich bitterns,and from the air of hay barns in Denmark.Five halotolerant strains were recognised as a hitherto un-described species Wallemia hederae,the phylogenetic sister of the halophilic W.ichthyophaga.Wallemia spp.show in-vitro growth on media that contain the chaotropic salt MgCl_(2).Wallemia ichthyophaga can grow in liquid medium enriched with 2 M MgCl_(2).Never before has a microorganism been grown on comparably high MgCl_(2) concentrations.Tests of the activity of a wide range of extracellular enzymes in the presence of NaCl also suggested that Wallemia iswell-adapted to substrates with a reduced water activity.
