Biology subjects

Kovi, M. R.

Publications and source records attributed to Kovi, M. R..

3 recordsLinked to original sources

bioRxiv2026

PhytoScan3D: an open-source Python pipeline for batch extraction of phenotypic traits from 3D point cloud files generated by multispectral plant phenotyping sensors

High-throughput 3D multispectral plant phenotyping platforms generate large volumes of point cloud files, but trait extraction is typically performed by sensor-bundled software whose internal algorithms are not publicly documented, which limits reproducibility and integration into custom research pipelines. Here we present PhytoScan3D, an open-source Python pipeline that extracts morphological and spectral phenotypic traits, spanning plant height, 3D leaf area, digital biomass, convex hull volume, leaf inclination, canopy geometry, NDVI, hue, and vegetation indices, from both PLY and PCD point cloud files generated by Phenospex PlantEye F500 and F600 sensors, and is portable to point clouds from any acquisition platform. PhytoScan3D was validated against HortControl (PhenoSpex) ground-truth measurements on 936 barley (Hordeum vulgare) pot-date observations from the growth chamber trial (20 Norwegian cultivars, 12 scan dates, Septemenr 2025 to January 2026), achieving Pearson r = 0.913 to 0.999 and ratio approximately 1.000 for Plant Height Max, 3D Leaf Area, and NDVI Average. A vectorised mesh face filtering implementation achieved a 120x speed improvement, increasing valid 3D Leaf Area coverage from 0.6% to 100% of files. Cross-format validation on 223 PlantEye F600 PCD files from the ICRISAT LeasyScan platform (four legume species: mungbean, cowpea, lima bean, and common bean; 1,523 plant observations) yielded r = 0.884 against independent cuboid annotation heights. The systematic positive bias (mean +27.2 mm, ratio = 1.44) is attributable to PhytoScan3D computing height from raw point cloud Z-range while cuboid annotations are fitted to segmented plant points only, with the offset consistent across all four species (per-species r = 0.880 to 0.888). Cross-dataset processing of 1,180 PLY files from the Crops3D benchmark (8 species, 3 acquisition methods) confirmed zero extraction errors. PhytoScan3D is available at "github.com/kovimallik/phytoscan3d" under the MIT licence and processes 1,651 files across three independent datasets in under 12 minutes on GPU hardware. HighlightsO_LIPhytoScan3D is the first open-source Python pipeline for batch extraction of phenotypic traits, including plant height, 3D leaf area, digital biomass, convex hull volume, leaf inclination, NDVI, and excess green index, from both PLY and PCD point cloud files generated by Phenospex PlantEye sensors. C_LIO_LIPrimary validation against HortControl ground-truth measurements on 936 barley pot-date observations achieved Pearson r = 0.913-0.999 for Plant Height Max, 3D Leaf Area, and NDVI Average. C_LIO_LIA 120x computational speedup in mesh face filtering (vectorised NumPy vs. set-based loop) increased the coverage of valid 3D Leaf Area extraction from 0.6% to 100% of files. C_LIO_LICross-format validation on 223 PlantEye F600 PCD files from ICRISAT LeasyScan (four legume species, 1,523 plants) achieved r = 0.884 against independent cuboid annotation heights. The systematic +27.2 mm bias reflects a methodological difference (raw Z-range vs. soil-segmented annotations), is consistent and predictable across all four species (per-species r = 0.880-0.888), and is correctable by a single linear factor. C_LIO_LICross-dataset processing of 1,180 PLY files from the Crops3D benchmark (8 species, 3 acquisition methods) confirmed zero extraction errors. C_LIO_LISignificant scan-unit variation was detected for Plant Height Max (F = 5.71, p < 0.001, 2 = 0.138) and Canopy Width X (F = 6.32, p < 0.001, 2 = 0.150), demonstrating the biological utility of extracted traits. C_LI

plant biology↗

bioRxiv2024

Surviving under Ice: Insights into gene-expression changes during ice encasement in timothy (Phleum pratense L.)

The predicted increase in frequency and duration of winter warming episodes (WWEs) at the higher northern latitudes is expected to negatively impact the forage production in this region. The formation of non-permeable ice cover due to WWEs creates hypoxic or anoxic conditions for plants leading to severe winter damages. Knowledge about molecular mechanisms underlying various winter stresses is crucial to develop cultivars with better winter survival under changing climatic conditions. In the current study, we aimed at identifying genes involved in ice encasement stress responses by RNAseq in the perennial forage grass timothy (Phleum pratense L.) and study gene expression differentiation due to field survival using cultivars with diverse genetic backgrounds. The LD50 estimates varied across cultivars and material. The expression of ethylene-responsive transcription factors, alcohol dehydrogenase, pyruvate decarboxylase, sucrose synthase, dehydrins, and heat shock proteins were highly upregulated under ice encasement conditions. Functional analysis of differentially expressed genes revealed that the upregulated genes were involved in glycolysis, pyruvate metabolism, carbon metabolism, and biosynthesis of amino acids while genes involved in photosynthesis, phenylpropanoid biosynthesis and flavonoid biosynthesis pathways were downregulated. The results from the current study indicate a substantial overlap of ice encasement stress responses with those of hypoxia and freezing stresses. In addition, the potential strategies leading to higher ice encasement tolerance of timothy are outlined. Furthermore, differences in gene expression between field survivors and the original plant material, and differences between ice encasement responses of northern-adapted and southern-adapted cultivars are briefly discussed.

plant biology↗

bioRxiv2019

ForageGrassBase: Molecular resource for the forage grass Festuca pratensis Huds.

BackgroundMeadow fescue (Festuca pratensis Huds.) is one of the most important forage grasses in temperate regions. F. pratensis is a diploid (2n =14) outbreeding species that belongs to the genus Festuca. Together with Lolium, they are the most important genera of forage grasses in temperate regions. F. pratensis has good winter survival, with high quality dry matter yields and persistency, and is suitable both for frequent-cutting conservation regimes and for grazing. It is a significant component of species-rich permanent pastures in the temperate regions, ensuring high forage yield under harsh climatic conditions where other productive forage grass species are unable to grow. However, genomic resources for F. Pratensis is not available so far.\n\nResultsThe draft genome sequences of two F. pratensis genotypes \"HF7/2\" and \"B14/16\" are reported in this study. Here, using the draft genome, functional annotation datasets of two F. pratensis cultivars, we have constructed the F. pratensis genome database http://foragegrass.org/, the first open-access platform to provide comprehensive genomic resources related to this forage grass species. The current version of this database provides the most up-to-date draft genome sequence along with structural and functional annotations for genes using Genome Browser (GBrowse). In addition, we have integrated comparative genomic tracks for F. pratensis genomes by mapping F.pratensis genome to the barley, rice, Brachypodium and maize genomes. We have integrated homologus search tool BLAST also for the users to analyze their data. Combined, GBrowse, BLAST and downloadble data gives an user friendly access to F. pratensis genomic resouces. All data in the database were manually curated.\n\nConclusionTo our knowledge, ForageGrassBase is the first genome database dedicated to forage grasses. It provides valuable resources for a range of research fields related to F. pratensis and other forage crop species, as well as for plant research communities in general. The genome database can be accessed at http://foragegrass.org. In the near future, we will expand the ForageGrassBase by adding genomic tools for other forage grass species, as soon as their genomes become available.

plant biology↗