Post di Dipartimento di Scienze Statistiche - Università di Roma "La Sapienza"​

Graduation completed Alhamdulillah. AGRICULTURE is more amazing if someone is natural like me. My specialization was in Plant Breeding and Genetics(PBG) in Agriculture, a major full of curiosities, science, and statistics. PBG means to deal with plants for changing their genetic architecture through conventional hybridization and molecular approaches for achieving valuable products from their phenotypes. PBG opens your mind to the thrust of knowledge and provides unlimited practice on theoretical and practical learning, no matter whether this practice belongs to a field or a lab. It was a golden era of transformation for me. Many new people in the form of teachers, seniors, mentors, juniors, friends, and family have been adding to my social circle. The golden thing that I have learned in the last 2 years is to hear others, accept their narrative, don't hate someone based on his/her narrative, and accept the bad things, they will also open a new path in your journey. At there, the journey is still not completed, moving forward in science keeps someone mentally young and active. Alhamdulillah #agriculture #PlantBreeding #science #fellinghappy

#PhD_Scholarship_to_both_UK_and_international_students_with_a_nice_salary_and_consumables_package# Funding Information This 4-year studentship/scholarship is #open to both UK and international students, covering enhanced stipends, tuition fees, as well as increased consumable and travel costs. Location: Edinburgh, United Kingdom Application Deadline: January 8, 2024 Field: Genetics Topic: Analyzing Genetic Changes in Holstein Cattle Populations About the Project The dairy cattle industry has seen significant advancements in selective breeding, particularly within Holstein cattle populations. This PhD project focuses on understanding the long-term genetic changes in Holstein cattle, addressing concerns about reduced genetic diversity due to intensive selection practices. Project Outline Work Package 1: Analyzing the genetic makeup of the global Holstein population. Work Package 2: Studying trends in genetic mean and variance for key Holstein traits. Work Package 3: Developing optimized breeding strategies at local and international scales. How to Apply Download the application form from the link below https://lnkd.in/gNmJp9sR Submit applications to RDSVS.PGR.Admin@ed.ac.uk. Ensure separate applications for multiple studentships if applying for more than one opportunity. #Goodluck#

👀 The PhD student from CRAG Nicole Pradas Ferazzoli along with her team (Federico Jurado Ruiz and Carles Onielfa) have developed PERSEUS, a new web-tool for pedigree visualizations through user-friendly, interactive graph networks. Perseus has been developed within the “GenoDrawIA” project led by Maria Jose Aranzana, IRTA (Instituto de Investigación y Tecnología Agroalimentarias) 🍐 The pedigrees rendered within this website tool have been retrieved from published works. In addition, passport data containing traits of relevance for each cultivar or accession are rendered alongside the graphs. 🍇 PERSEUS is currently focused on five of the most economically important crops: apple, almond, pear, grapevine and peach, but it has the potential for expansion to other species and inclusion of genomic marker data. Pedigree data is of crucial relevance in research studies and breeding. 👉 Check the website of this tool here: https://lnkd.in/epz-u_3r

It is no novelty that repeated measures require special treatment in data analysis. Nevertheless, this is often overlooked by plant breeders, keeping them from reaching higher genetic gains. In our new paper, we demonstrate how properly accounting for the effects' heterogeneity using covariance structuring provides benefits for the selection of candidates with high and predictable performance. We show how the factor analytic covariance structuring on the genetic effects, and the factor analytic selection tools can be useful in repeated measures context. We also introduce a new metric for selecting the best factor analytic mixed model based on the total semivariances, which considers not only the variance but also the covariances explained by the model. This was all applied to a real dataset with phenotypic records of nine consecutive years of cupuassu (Theobroma grandiflorum), an Amazonian native species. Given the benefits and novelties proposed, we discuss how the cupuassu breeding programme can use these resources to reach higher standards. Please, contact me if you want to discuss our results, and use this link to access the read-only version: https://lnkd.in/dAMUpxaV. Do not forget to have a look at the supplementary information, where we added the detailed results of each tested model and the R codes used to generate it: https://lnkd.in/d7qTJfqq The data set and R codes used to perform the analyses are freely available at https://lnkd.in/dH8ZEKeK This paper was made after the second chapter of my dissertation, so there are a lot of people to whom I am grateful. A special thanks to the co-authors, namely Professor Kaio Olimpio, Dr Rodrigo Alves, Dr Rafael Moyses Alves - Embrapa Amazonia Oriental, Professor Luiz Dias, and Dr Jeniffer Santana Pinto Coelho Evangelista, who directly contributed to building this paper. #data #dataanalysis #grateful

This study emphasizes the importance of considering repeated measures in data analysis, especially in the field of plant breeding. Using ASReml-R 4.1 the authors highlight the benefits of accounting for the heterogeneity of effects through covariance structuring. This approach enables the selection of candidates with consistent and superior performance, leading to higher genetic gains. And if you thought ASReml-R 4.1 was good wait until you see the gains with ASReml-R 4.2!! #asreml #statistics #dataanalysis #plantbreeding #animalbreeding