Evidence map›Paper›PMID 38353850›Full record

ArticleJournal of applied genetics2024

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

Piotr Stefański, Sajid Ullah, Przemysław Matysik, Krystyna Rybka

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Article in Journal of applied genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Piotr StefańskiPlant Breeding Strzelce Ltd. Co. IHAR Group, 99-307, Strzelce, Poland.
Sajid UllahFaculty of Science, National Centre for Biomolecular Research, Masaryk University, Brno, Czech Republic.
Przemysław MatysikPlant Breeding Strzelce Ltd. Co. IHAR Group, 99-307, Strzelce, Poland.
Krystyna RybkaPlant Breeding and Acclimatization Institute-National Research Institute, IHAR-PIB, Biochemistry and Biotechnology Department, 05-870, Radzików, Poland. k.rybka@ihar.edu.pl.ORCID http://orcid.org/0000-0002-4707-8492

Funding

Ministerstvo Školství, Mládeže a Tělovýchovy CZ.02.1.01/0.0/0.0/16_026/0008446Narodowe Centrum Badań i Rozwoju POIR-01.01.01-00-0782/16-00
6 · The paper itself

Abstract

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.

Indexed as

TriticaleEdible GrainPlant BreedingProspective StudiesSoilSoilDeep learningEar detectionField imagingPlant breedingStatistical analysisYield potential

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.