AIMC Topic: Solanum lycopersicum

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Intact Detection of Highly Occluded Immature Tomatoes on Plants Using Deep Learning Techniques.

Sensors (Basel, Switzerland) May 25, 2020
Automatic detection of intact tomatoes on plants is highly expected for low-cost and optimal management in tomato farming. Mature tomato detection has been wildly studied, while immature tomato detection, especially when occluded with leaves, is diff...
Image Processing, Computer-Assisted Solanum lycopersicum Fruit Neural Networks, Computer Deep Learning
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Identification of Tomato Disease Types and Detection of Infected Areas Based on Deep Convolutional Neural Networks and Object Detection Techniques.

Computational intelligence and neuroscience Dec 16, 2019
This study develops tomato disease detection methods based on deep convolutional neural networks and object detection models. Two different models, Faster R-CNN and Mask R-CNN, are used in these methods, where Faster R-CNN is used to identify the typ...
Plant Diseases Pattern Recognition, Automated Image Processing, Computer-Assisted Solanum lycopersicum Fruit Neural Networks, Computer Machine Learning
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Machine Learning Approaches to Improve Three Basic Plant Phenotyping Tasks Using Three-Dimensional Point Clouds.

Plant physiology Oct 7, 2019
Developing automated methods to efficiently process large volumes of point cloud data remains a challenge for three-dimensional (3D) plant phenotyping applications. Here, we describe the development of machine learning methods to tackle three primary...
Phenotype Plant Stems Reproducibility of Results Plant Shoots Imaging, Three-Dimensional Machine Learning Environment Solanum lycopersicum Nicotiana Plant Leaves Algorithms Plants Plant Roots
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Design of a tomato classifier based on machine vision.

PloS one Jul 18, 2019
This paper attempts to design an automated, efficient and intelligent tomato grading method that facilitates the graded selling of the fruit. Based on machine vision, the color images of tomatoes with different morphologies were studied, and the colo...
Solanum lycopersicum Phenotype Reproducibility of Results Humans Machine Learning Algorithms
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Combined network analysis and machine learning allows the prediction of metabolic pathways from tomato metabolomics data.

Communications biology Jun 18, 2019
The identification and understanding of metabolic pathways is a key aspect in crop improvement and drug design. The common approach for their detection is based on gene annotation and ontology. Correlation-based network analysis, where metabolites ar...
Machine Learning Metabolomics Metabolic Networks and Pathways Solanum lycopersicum
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A Mature-Tomato Detection Algorithm Using Machine Learning and Color Analysis.

Sensors (Basel, Switzerland) Apr 30, 2019
An algorithm was proposed for automatic tomato detection in regular color images to reduce the influence of illumination and occlusion. In this method, the Histograms of Oriented Gradients (HOG) descriptor was used to train a Support Vector Machine (...
Machine Learning Algorithms Biosensing Techniques Humans Solanum lycopersicum Support Vector Machine Color
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Research and analysis of cadmium residue in tomato leaves based on WT-LSSVR and Vis-NIR hyperspectral imaging.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 29, 2018
The reliability and validity of Vis-NIR hyperspectral imaging were investigated for the determination of heavy metal content in tomato leaves under different cadmium stress. Besides, a method involving wavelet transform and least square support vecto...
Plant Leaves Principal Component Analysis Least-Squares Analysis Reproducibility of Results Solanum lycopersicum Spectroscopy, Near-Infrared Cadmium Support Vector Machine Wavelet Analysis
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Sanitation of tomatoes based on a combined approach of washing process and pulsed light in conjunction with selected disinfectants.

Food research international (Ottawa, Ont.) Sep 10, 2018
In this study, we evaluated the performance of a large-scale decontamination system based on a washing process in combination with pulsed light (PL) exposure and HO/chlorine. In order to identify optimum processing condition, we first evaluated the e...
Sanitation Decontamination Salmonella Food Poisoning Fruit Food Microbiology Hydrogen Peroxide Disinfectants Chlorine Solanum lycopersicum Water Salmonella enterica Light Food Handling
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Consistent prediction of GO protein localization.

Scientific reports May 17, 2018
The GO-Cellular Component (GO-CC) ontology provides a controlled vocabulary for the consistent description of the subcellular compartments or macromolecular complexes where proteins may act. Current machine learning-based methods used for the automat...
Gene Ontology Arabidopsis Databases, Protein Solanum lycopersicum Computational Biology Saccharomyces cerevisiae Software Proteomics Drosophila melanogaster Animals Proteins Molecular Sequence Annotation
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Modelling the water-plant cuticular polymer matrix membrane partitioning of diverse chemicals in multiple plant species using the support vector machine-based QSAR approach.

SAR and QSAR in environmental research Jan 18, 2018
In this study, a support vector machine (SVM) based multi-species QSAR (quantitative structure-activity relationship) model was developed for predicting the water-plant cuticular polymer matrix membrane (MX) partition coefficient, K of diverse chemic...
Water Support Vector Machine Solanum lycopersicum Quantitative Structure-Activity Relationship Plant Stomata Models, Molecular Polymers Environmental Pollutants
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