J 2024

Triticale field phenotyping using RGB camera for ear counting and yield estimation

STEFAŃSKI, Piotr, Sajid ULLAH, Przemysław MATYSIK and Krystyna RYBKA

Basic information

Original name

Triticale field phenotyping using RGB camera for ear counting and yield estimation

Authors

STEFAŃSKI, Piotr, Sajid ULLAH (586 Pakistan, belonging to the institution), Przemysław MATYSIK and Krystyna RYBKA

Edition

Journal of Applied Genetics, Springer, 2024, 1234-1983

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10611 Plant sciences, botany

Country of publisher

Germany

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

URL

Impact factor

Impact factor: 2.400 in 2022

Organization unit

Faculty of Science

DOI

http://dx.doi.org/10.1007/s13353-024-00835-6

UT WoS

001161689400002

Keywords in English

plant breeding; yield potential; ear detection; deep learning; field imaging; statistical analysis

Tags

rivok

Tags

International impact, Reviewed
Změněno: 16/4/2024 11:09, Mgr. Marie Šípková, DiS.

Abstract

V originále

Triticale (X Triticosecale Wittmack), a wheat-rye small grain crop hybrid, combines wheat and rye attributes in one hexaploid genome. It is characterized by high adaptability to adverse environmental conditions: drought, soil acidity, salinity and heavy metal ions, poorer soil quality, and waterlogging. So that its cultivation is prospective in a changing climate. Here, we describe RGB on-ground phenotyping of field-grown eighteen triticale market-available cultivars, made in naturally changing light conditions, in two consecutive winter cereals growing seasons: 2018–2019 and 2019–2020. The number of ears was counted on top-down images with an accuracy of 95% and mean average precision (mAP) of 0.71 using advanced object detection algorithm YOLOv4, with ensemble modeling of field imaging captured in two different illumination conditions. A correlation between the number of ears and yield was achieved at the statistical importance of 0.16 for data from 2019. Results are discussed from the perspective of modern breeding and phenotyping bottleneck.

Links

EF16_026/0008446, research and development project
Name: Integrace signálu a epigenetické reprogramování pro produktivitu rostlin
Displayed: 19/11/2024 15:55