Table of Contents
Agronomy, Volume 10, Issue 2 (February 2020) – 163 articles
- Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.
- You may sign up for e-mail alerts to receive table of contents of newly released issues.
- PDF is the official format for papers published in both, html and pdf forms. To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them.
Cover Story (view full-size image) Conventional methods for leaf area index (LAI) estimation are laborious and time-consuming, so it [...] Read more. Conventional methods for leaf area index (LAI) estimation are laborious and time-consuming, so it is not often determined in plant breeding trials where hundreds of cultivars are evaluated at the same time. The recent emergence of high-throughput plant phenotyping platforms has increased the need to develop new phenotyping tools to foster decision-making by breeders. The combination of artificial intelligence algorithms and nadir-view RGB images taken from a terrestrial high throughput phenotyping platform has allowed to develop a novel methodology to make rapid and accurate LAI estimations in wheat breeding trials. Model-based LAI estimations were validated against LAI measurements determined non-destructively using an allometric relationship obtained in this study and against a classical indirect method based on bottom-up hemispherical images and gaps fraction theory. View this paper