Biology subjects

Visioni, A.

Publications and source records attributed to Visioni, A..

3 recordsLinked to original sources

bioRxiv2025

The Global Wheat Full Semantic Organ Segmentation (GWFSS) dataset

Computer vision is increasingly used in farmers fields and agricultural experiments to quantify important traits. Imaging setups with a sub-millimetre ground sampling distance enable the detection and tracking of plant features, including size, shape, and colour. Although todays AI-driven foundation models segment almost any object in an image, they still fail for complex plant canopies. To improve model performance, the global wheat dataset consortium assembled a diverse set of images from experiments around the globe. After the head detection dataset (GWHD), the new dataset targets a full semantic segmentation (GWFSS) of wheat organs (leaves, stems and spikes) covering all developmental stages. Images were collected by 11 institutions using a wide range of imaging setups. Two datasets are provided: i) a set of 1096 diverse images in which all organs were labelled at the pixel level, and (ii) a dataset of 52,078 images without annotations available for additional training. The labelled set was used to train segmentation models based on DeepLabV3Plus and Segformer. Our Segformer model performed slightly better than DeepLabV3Plus with a mIOU for leaves and spikes of ca. 90%. However, the precision for stems with 54% was rather lower. The major advantages over published models are: i) the exclusion of weeds from the wheat canopy, ii) the detection of all wheat features including necrotic and senescent tissues and its separation from crop residues. This facilitates further development in classifying healthy vs. unhealthy tissue to address the increasing need for accurate quantification of senescence and diseases in wheat canopies.

plant biology↗

bioRxiv2024

New loci and candidate genes in spring two-rowed barley detected through meta-analysis of a field trial European network

This study contributes new knowledge on quantitative trait loci (QTLs) and candidate genes for adaptive traits and yield in two-rowed spring barley. A meta-analysis of a network of field trials, varying in latitude and sowing date, with 151 cultivars across several European countries, increased QTL detection power compared to single-trial analyses. The traits analysed were heading date (HD), plant height (PH), thousand-grain weight (TGW), and grain yield (GY). Breaking down the analysis by the main genotype-by-environment trends revealed QTLs and candidate genes specific to conditions like sowing date and latitude. A historical look on the evolution of QTL frequencies revealed that early selection focused on PH and TGW, likely due to their high heritability. GY selection occurred later, facilitated by reduced variance in other traits. The study observed that favourable alleles for plant height were often fixed before those for grain yield and TGW. Some regions showed linkage in repulsion, suggesting targets for future breeding. Several candidate genes were identified, including known genes and new candidates based on orthology with rice. Remarkably, the deficiens allele of gene Vrs1, appears associated to higher GY. These findings provide valuable insights for barley breeders aiming to improve yield, and other agronomic traits. HighlightA dense genome-wide meta-analysis provides new QTLs, reveals breeding history trends and identifies new candidate genes for yield, plant height, grain weight and heading time of spring barley.

genetics↗

bioRxiv2022

CGIAR BARLEY BREEDING TOOLBOX: A diversity panel to facilitate breeding and genomic research in the Developing World

Despite the reduced cost of the new genotyping technologies, many public and private breeding programs, mostly in developing countries, still cannot afford them, hindering their research. The objective of the present study was to identify and assemble an Association Mapping panel of widely diverse barley genotypes to serve as a barley breeding toolbox, especially for the Developing World. The main criteria were: i) to be representative of the germplasm grown in the Developing World; ii) to cover a wide range of genetic variability and iii) to be of public domain. For it, we assembled and genotyped a Global Barley Panel (GBP) of 530 genotypes representing a wide range of row-types, end-uses, growth habits, geographical origins and environmental conditions. The GBP accessions were genotyped using the barley Infinium iSelect 50K chip. A total of 40,342 SNP markers were polymorphic and displayed an average polymorphism information content (PIC) of 0.35, with 66% of them exceeding PIC=0.25. The analysis of the population structure identified 8 sub-populations mostly linked to the geographical origin of the lines (Europe, Australia, USA, Canada, Africa, Latin-America, ICARDA and others), four of them of significant ICARDA origin. The 16 allele combinations at 4 major flowering genes (HvVRN-H3, HvPPD-H1, HvVRN-H1 and HvCEN) explained 11.07% genetic variation and were linked to the geographic origins of the lines studied. Among origins, ICARDA material (n= 257) showed wide diversity as revealed by the highest number of polymorphic loci (99.76% of all polymorphic SNPs in GBP), number of private alleles and Neis gene diversity and the fact that ICARDA lines were present in all 8 sub-populations and carried all 16 allelic combinations at phenology genes. Due to their genetic diversity and their representativity of the germplasm adapted to the Developing World, 312 ICARDA lines and cultivated landraces were pre-selected to form the CGIAR Barley Breeding Toolbox (CBBT). Using the genotypic data and the Mean of Transformed Kinships method, we assembled the CBBT, an Association Mapping panel of 250 accessions capturing most of the allelic diversity in the global panel. The CBBT preserves a good balance between row types as well as a good representation of both allelic combinations identified at most important phenological loci and sub-populations of the GBP. The CBBT lines together with their genotypic data will be made available to breeders and researchers worldwide to serve as a collaborative tool to underpin the genetic mechanisms of traits of interest for barley cultivation.

genetics↗